Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2014 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
   6  #                                                                             # 
   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  17  # GNU General Public License for more details.                                # 
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  21  #                                                                             # 
  22  ############################################################################### 
  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  from numpy import array, asarray, exp, median, inf, log, save, std, sum, zeros 
  27  from minfx.generic import generic_minimise 
  28  from random import gauss 
  29  import re, math 
  30  from tempfile import mkdtemp, NamedTemporaryFile 
  31   
  32   
  33  # relax module imports. 
  34  from auto_analyses import relax_disp 
  35  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  36  from data_store import Relax_data_store; ds = Relax_data_store() 
  37  import dep_check 
  38  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_ANALYTIC_CPMG, MODEL_LIST_FULL, MODEL_LIST_NUMERIC_CPMG, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  39  from lib.errors import RelaxError 
  40  from lib.io import extract_data, get_file_path, open_read_file 
  41  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  42  from pipe_control.mol_res_spin import display_spin, generate_spin_string, return_spin, spin_loop 
  43  from pipe_control.minimise import assemble_scaling_matrix 
  44  from pipe_control.pipes import display 
  45  from specific_analyses.relax_disp.checks import check_missing_r1 
  46  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  47  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, has_r1rho_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_exp_frq_offset_point_time, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  48  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  49  from specific_analyses.relax_disp.model import models_info, nesting_param 
  50  from specific_analyses.relax_disp.parameters import linear_constraints 
  51  from status import Status; status = Status() 
  52  from test_suite.system_tests.base_classes import SystemTestCase 
  53   
  54  # C modules. 
  55  if dep_check.C_module_exp_fn: 
  56      from specific_analyses.relax_fit.optimisation import func_wrapper, dfunc_wrapper, d2func_wrapper 
  57      from target_functions.relax_fit import jacobian, jacobian_chi2, setup 
  58      # Call the python wrapper function to help with list to numpy array conversion. 
  59      func = func_wrapper 
  60      dfunc = dfunc_wrapper 
  61      d2func = d2func_wrapper 
  62   
  63   
  64 -class Relax_disp(SystemTestCase): 
  65      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  66   
  67 -    def __init__(self, methodName='runTest'): 
  68          """Skip certain tests if the C modules are non-functional. 
  69   
  70          @keyword methodName:    The name of the test. 
  71          @type methodName:       str 
  72          """ 
  73   
  74          # Execute the base class method. 
  75          super(Relax_disp, self).__init__(methodName) 
  76   
  77          # Tests to skip. 
  78          blacklist = [ 
  79              'test_m61b_data_to_m61b' 
  80          ] 
  81          if methodName in blacklist: 
  82              status.skipped_tests.append([methodName, None, self._skip_type]) 
  83   
  84          # Missing module. 
  85          if not dep_check.C_module_exp_fn: 
  86              # The list of tests to skip. 
  87              to_skip = [ 
  88                  "test_bug_atul_srivastava", 
  89                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  90                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  91                  "test_estimate_r2eff_err", 
  92                  "test_estimate_r2eff_err_auto", 
  93                  "test_estimate_r2eff_err_methods", 
  94                  "test_finite_value", 
  95                  "test_exp_fit", 
  96                  "test_m61_exp_data_to_m61", 
  97                  "test_r1rho_kjaergaard_auto", 
  98                  "test_r1rho_kjaergaard_auto_check_graphs", 
  99                  "test_r1rho_kjaergaard_man", 
 100                  "test_r1rho_kjaergaard_missing_r1", 
 101                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
 102              ] 
 103   
 104              # Store in the status object. 
 105              if methodName in to_skip: 
 106                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
 107   
 108          # If not scipy.optimize.leastsq. 
 109          if not dep_check.scipy_module: 
 110              # The list of tests to skip. 
 111              to_skip = [ 
 112                  "test_estimate_r2eff_err_methods" 
 113              ] 
 114   
 115              # Store in the status object. 
 116              if methodName in to_skip: 
 117                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 118   
 119          # If not NMRPipe showApod program in PATH. 
 120          if not dep_check.showApod_software: 
 121              # The list of tests to skip. 
 122              to_skip = [ 
 123                  "test_show_apod_extract", 
 124                  "test_show_apod_rmsd", 
 125                  "test_show_apod_rmsd_to_file", 
 126                  "test_show_apod_rmsd_dir_to_files" 
 127              ] 
 128   
 129              # Store in the status object. 
 130              if methodName in to_skip: 
 131                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 132   
 133          # If not matplotlib module 
 134          if not dep_check.matplotlib_module: 
 135              # The list of tests to skip. 
 136              to_skip = [ 
 137                  "test_repeat_cpmg" 
 138              ] 
 139   
 140              # Store in the status object. 
 141              if methodName in to_skip: 
 142                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 143   
 144   
 145 -    def setUp(self): 
 146          """Set up for all the functional tests.""" 
 147   
 148          # Create the data pipe. 
 149          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 150   
 151          # Create a temporary directory for dumping files. 
 152          ds.tmpdir = mkdtemp() 
 153          self.tmpdir = ds.tmpdir 
 154   
 155   
 156 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 157          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 158   
 159          @keyword folder:            The name of the folder for the test data. 
 160          @type folder:               str 
 161          @keyword model_analyse:     The name of the model which will be tested. 
 162          @type model_analyse:        str 
 163          """ 
 164   
 165          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 166   
 167          # Data. 
 168          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 169   
 170          ## Experiments 
 171          # Exp 1 
 172          sfrq_1 = 500.0*1E6 
 173          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 174          time_T2_1 = 0.05 
 175          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 176          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 177          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 178          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 179          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 180   
 181          sfrq_2 = 600.0*1E6 
 182          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 183          time_T2_2 = 0.06 
 184          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 185          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 186          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 187          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 188          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 189   
 190          sfrq_3 = 700.0*1E6 
 191          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 192          time_T2_3 = 0.07 
 193          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 194          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 195          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 196          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 197          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 198   
 199          # Collect all exps 
 200          exps = [exp_1, exp_2, exp_3] 
 201   
 202          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 203          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 204          pA_arr = [0.9] 
 205          kex_arr = [1000.] 
 206   
 207          spins = [ 
 208                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 209                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 210                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 211                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 212                  ] 
 213   
 214          # Create the data pipe. 
 215          pipe_name = 'base pipe' 
 216          pipe_type = 'relax_disp' 
 217          pipe_bundle = 'relax_disp' 
 218          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 219   
 220          # Generate the sequence. 
 221          for res_name, res_num, spin_name, params in spins: 
 222              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 223   
 224          # Set isotope 
 225          self.interpreter.spin.isotope('15N', spin_id='@N') 
 226   
 227          # Now loop over the experiments, to set the variables in relax. 
 228          exp_ids = [] 
 229          for exp_i in exps: 
 230              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 231              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 232              exp_ids.append(exp_id) 
 233   
 234              ids = [] 
 235              for ncyc in ncycs: 
 236                  nu_cpmg = ncyc / time_T2 
 237                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 238                  ids.append(cur_id) 
 239   
 240                  # Set the spectrometer frequency. 
 241                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 242   
 243                  # Set the experiment type. 
 244                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 245   
 246                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 247                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 248   
 249                  # Set the relaxation dispersion CPMG frequencies. 
 250                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 251   
 252          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 253   
 254          ### Now do fitting. 
 255          # Change pipe. 
 256   
 257          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 258          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 259          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 260   
 261          # Now read data in. 
 262          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 263              exp_id = exp_ids[mi] 
 264              exp_i = exps[mi] 
 265              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 266   
 267              # Then loop over the spins. 
 268              for res_name, res_num, spin_name, params in spins: 
 269                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 270   
 271                  # Define file name 
 272                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 273   
 274                  # Read in the R2eff file to put into spin structure. 
 275                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 276   
 277          # Then select model. 
 278          self.interpreter.relax_disp.select_model(model=model_analyse) 
 279   
 280          # Then cluster 
 281          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 282   
 283          # Grid search 
 284          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 285          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 286   
 287          # Then loop over the defined spins and read the parameters. 
 288          for i in range(len(spins)): 
 289              res_name, res_num, spin_name, params = spins[i] 
 290              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 291              cur_spin = return_spin(cur_spin_id) 
 292   
 293              for mo_param in cur_spin.params: 
 294                  print(mo_param) 
 295                  # The R2 is a dictionary, depending on spectrometer frequency. 
 296                  if isinstance(getattr(cur_spin, mo_param), dict): 
 297                      for key, val in getattr(cur_spin, mo_param).items(): 
 298                          should_be = params[mo_param][key] 
 299                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 300                          self.assertAlmostEqual(val, should_be) 
 301                  else: 
 302                      should_be = float(params[mo_param]) 
 303                      val = getattr(cur_spin, mo_param) 
 304                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 305                      self.assertAlmostEqual(val, should_be) 
 306   
 307              # Test chi2. 
 308              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 309              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 310   
 311   
 312 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 313          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 314   
 315          # The path to the data files. 
 316          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 317   
 318          # Set pipe name, bundle and type. 
 319          ds.pipe_name = 'base pipe' 
 320          ds.pipe_bundle = 'relax_disp' 
 321          ds.pipe_type = 'relax_disp' 
 322   
 323          # Create the data pipe. 
 324          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 325   
 326          # Read the spins. 
 327          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 328   
 329          # Name the isotope for field strength scaling. 
 330          self.interpreter.spin.isotope(isotope='15N') 
 331   
 332          # Set number of experiments to be used. 
 333          NR_exp = 70 
 334   
 335          # Load the experiments settings file. 
 336          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 337          expfileslines = expfile.readlines()[:NR_exp] 
 338          expfile.close() 
 339   
 340          # In MHz 
 341          yOBS = 81.050 
 342          # In ppm 
 343          yCAR = 118.078 
 344          centerPPM_N15 = yCAR 
 345   
 346          ## Read the chemical shift data. 
 347          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 348   
 349          # The lock power to field, has been found in an calibration experiment. 
 350          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 351   
 352          # Apply spectra settings. 
 353          # Count settings 
 354          j = 0 
 355          for i in range(len(expfileslines)): 
 356              line = expfileslines[i] 
 357              if line[0] == "#": 
 358                  continue 
 359              else: 
 360                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 361                  DIRN = line.split()[0] 
 362                  I = int(line.split()[1]) 
 363                  deltadof2 = line.split()[2] 
 364                  dpwr2slock = line.split()[3] 
 365                  ncyc = int(line.split()[4]) 
 366                  trim = float(line.split()[5]) 
 367                  ss = int(line.split()[6]) 
 368                  set_sfrq = float(line.split()[7]) 
 369                  apod_rmsd = float(line.split()[8]) 
 370                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 371   
 372                  # Calculate spin_lock time 
 373                  time_sl = 2*ncyc*trim 
 374   
 375                  # Define file name for peak list. 
 376                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 377                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 378   
 379                  # Load the peak intensities. 
 380                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 381   
 382                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 383                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 384   
 385                  # Set the relaxation dispersion experiment type. 
 386                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 387   
 388                  # Set The spin-lock field strength, nu1, in Hz 
 389                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 390   
 391                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 392                  frq_N15_Hz = yOBS * 1E6 
 393                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 394                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 395   
 396                  # Set The spin-lock offset, omega_rf, in ppm. 
 397                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 398   
 399                  # Set the relaxation times (in s). 
 400                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 401   
 402                  # Set the spectrometer frequency. 
 403                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 404   
 405                  # Add to counter 
 406                  j += 1 
 407   
 408   
 409          print("Testing the number of settings") 
 410          print("Number of settings iterations is: %s. Number of cdp.exp_type.keys() is: %s"%(i, len(cdp.exp_type.keys() ) ) ) 
 411          self.assertEqual(70, len(expfileslines)) 
 412          self.assertEqual(69, j) 
 413          self.assertEqual(69, len(cdp.exp_type.keys()) ) 
 414   
 415          # Cluster spins 
 416          for curspin in cluster_ids: 
 417              print("Adding spin %s to cluster"%curspin) 
 418              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 419   
 420          # De-select for analysis those spins who have not been clustered 
 421          for free_spin in cdp.clustering['free spins']: 
 422              print("Deselecting free spin %s"%free_spin) 
 423              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 424   
 425   
 426          #Paper         reference values 
 427          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 428          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 429          ds.ref = dict() 
 430          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 431          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 432          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 433          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 434          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 435          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 436          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 437          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 438          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 439          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 440          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 441          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 442          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 443          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 444          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 445   
 446          ds.guess = dict() 
 447          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 448          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 449          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 450          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 451          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 452          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 453          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 454          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 455          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 456          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 457          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 458          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 459          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 460          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 461          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 462   
 463          # Assign guess values. 
 464          for spin, spin_id in spin_loop(return_id=True): 
 465              if spin_id in cluster_ids: 
 466                  print("spin_id %s in cluster ids"%(spin_id)) 
 467                  spin.kex = ds.guess[spin_id][6] 
 468                  spin.phi_ex = ds.guess[spin_id][10] 
 469              else: 
 470                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 471   
 472          if read_R1: 
 473              # Read the R1 data 
 474              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 475   
 476   
 477 -    def setup_hansen_cpmg_data(self, model=None): 
 478          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 479   
 480          @keyword model: The name of the model which will be tested. 
 481          @type model:    str 
 482          """ 
 483   
 484          # Create the data pipe and load the base data. 
 485          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 486          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 487          self.interpreter.results.read(data_path+sep+'base_pipe') 
 488          self.interpreter.deselect.spin(':4') 
 489   
 490          # Set the nuclear isotope data. 
 491          self.interpreter.spin.isotope('15N') 
 492   
 493          # Create the R2eff data pipe and load the results. 
 494          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 495          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 496          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 497          self.interpreter.deselect.spin(':4') 
 498   
 499          # The model data pipe. 
 500          pipe_name = "%s - relax_disp" % model 
 501          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 502          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 503   
 504          # Set the model. 
 505          self.interpreter.relax_disp.select_model(model=model) 
 506   
 507          # Copy the data. 
 508          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 509   
 510   
 511 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 512          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 513   
 514          @keyword model: The name of the model which will be tested. 
 515          @type model:    str 
 516          """ 
 517   
 518          # Create the data pipe and load the base data. 
 519          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 520          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 521          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 522   
 523          # Create the R2eff data pipe and load the results. 
 524          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 525          self.interpreter.pipe.switch(pipe_name='R2eff') 
 526          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 527   
 528          # The model data pipe. 
 529          pipe_name = "%s - relax_disp" % model 
 530          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 531          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 532   
 533          # Set the model. 
 534          self.interpreter.relax_disp.select_model(model=model) 
 535   
 536          # Copy the data. 
 537          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 538   
 539   
 540 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 541          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 542   
 543          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 544   
 545              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 546   
 547          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 548   
 549   
 550          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 551          @type data_list:    list of str 
 552          """ 
 553   
 554          # Create the data pipe and load the base data. 
 555          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 556          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 557   
 558          # Create the spin system. 
 559          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 560          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 561          self.interpreter.spin.element('H', spin_id='@H') 
 562          self.interpreter.spin.element('N', spin_id='@N') 
 563          self.interpreter.spin.isotope('1H', spin_id='@H') 
 564          self.interpreter.spin.isotope('15N', spin_id='@N') 
 565   
 566          # Define the magnetic dipole-dipole relaxation interaction. 
 567          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 568   
 569          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 570          data = [ 
 571              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 572              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 573              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 574              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 575              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 576              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 577              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 578              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 579              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 580              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 581              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 582              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 583              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 584              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 585              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 586              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 587              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 588              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 589          ] 
 590          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 591          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 592          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 593          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 594          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 595          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 596   
 597          # Loop over the files, reading in the data. 
 598          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 599              # Skip undesired data. 
 600              if data_type not in data_list: 
 601                  continue 
 602   
 603              # Alias the CPMG frequencies. 
 604              if data_type == 'SQ': 
 605                  cpmg_frqs = cpmg_frqs_sq 
 606              elif data_type == '1H SQ': 
 607                  cpmg_frqs = cpmg_frqs_1h_sq 
 608              elif data_type == 'DQ': 
 609                  cpmg_frqs = cpmg_frqs_dq 
 610              elif data_type == 'ZQ': 
 611                  cpmg_frqs = cpmg_frqs_zq 
 612              elif data_type == '1H MQ': 
 613                  cpmg_frqs = cpmg_frqs_1h_mq 
 614              elif data_type == 'MQ': 
 615                  cpmg_frqs = cpmg_frqs_mq 
 616   
 617              # Loop over each CPMG frequency. 
 618              for cpmg_frq in cpmg_frqs: 
 619                  # The id. 
 620                  new_id = "%s_%s" % (id, cpmg_frq) 
 621   
 622                  # Set the NMR field strength. 
 623                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 624   
 625                  # Set the relaxation dispersion experiment type. 
 626                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 627   
 628                  # Relaxation dispersion CPMG constant time delay T (in s). 
 629                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 630   
 631                  # Set the CPMG frequency. 
 632                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 633   
 634              # Read the R2eff data. 
 635              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 636   
 637          # Change the model. 
 638          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 639   
 640   
 641 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 642          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 643   
 644          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 645          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 646   
 647          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 648          Data is for experiment at 25 degree Celcius. 
 649          """ 
 650   
 651          # Create the data pipe and load the base data. 
 652          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 653   
 654          # Set experiment settings. sfrq, time_T2, ncyc 
 655          Exps = [ 
 656          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 657          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 658   
 659          # Create base pipe 
 660          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 661   
 662          # Loop throug experiments 
 663          id_lists = [] 
 664          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 665              # Read spins 
 666              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 667              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 668   
 669              # Make spectrum id list 
 670              id_list = list(key+str(i) for i in range(len(ncycs))) 
 671              id_lists.append(id_list) 
 672   
 673              # Read intensities 
 674              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 675   
 676              # Loop over experiments 
 677              for i in range(len(ncycs)): 
 678                  ncyc = ncycs[i] 
 679                  vcpmg = ncyc/time_T2 
 680   
 681                  # Test if spectrum is a reference 
 682                  if float(vcpmg) == 0.0: 
 683                      vcpmg = None 
 684                  else: 
 685                      vcpmg = round(float(vcpmg), 3) 
 686   
 687                  # Set current id 
 688                  current_id = id_list[i] 
 689   
 690                  # Set the current experiment type. 
 691                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 692   
 693                  # Set the NMR field strength of the spectrum. 
 694                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 695   
 696                  # Relaxation dispersion CPMG constant time delay T (in s). 
 697                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 698   
 699                  # Set the relaxation dispersion CPMG frequencies. 
 700                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 701   
 702          # Define replicated 
 703          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 704          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 705   
 706          # Perform error analysis 
 707          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 708          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 709   
 710          # Define isotope 
 711          self.interpreter.spin.isotope(isotope='15N') 
 712   
 713          ############# 
 714   
 715          # Define the 64 residues which was used for Global fitting 
 716          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 717          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 718          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 719          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 720          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 721          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 722   
 723          # Test number of global 
 724          self.assertEqual(64, len(glob_assn )) 
 725   
 726          ## Turn assignments into relax spin ids. 
 727          # Define regular expression search 
 728          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 729   
 730          # Create list to hold regular expression search 
 731          relax_glob_ids = [] 
 732   
 733          # Loop over assignments 
 734          for assn in glob_assn: 
 735              # Make match for the regular search 
 736              m = r.match(assn) 
 737              # Convert to relax spin string 
 738              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 739   
 740              # Save the relax spin string and the regular search 
 741              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 742   
 743          ############# Deselect all spins, and select few spins 
 744   
 745          ## Deselect all spins, and select a few for analysis 
 746          self.interpreter.deselect.all() 
 747   
 748          # Select few spins 
 749          for i in select_spin_index: 
 750              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 751   
 752          ############## 
 753   
 754          # Prepare for R2eff calculation 
 755          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 756          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 757   
 758          # Select model for points calculation 
 759          MODEL = "R2eff" 
 760          self.interpreter.relax_disp.select_model(model=MODEL) 
 761          # Calculate R2eff values 
 762          self.interpreter.minimise.calculate(verbosity=1) 
 763   
 764   
 765 -    def setup_missing_r1_spins(self): 
 766          """Function for setting up a few spins for the given pipe.""" 
 767   
 768          # Path to file. 
 769          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 770   
 771          # File with spins. 
 772          file = open(data_path+sep+'R1_fitted_values.txt') 
 773          lines = file.readlines() 
 774          file.close() 
 775   
 776          for i, line in enumerate(lines): 
 777              # Make the string test 
 778              line_split = line.split() 
 779   
 780              if line_split[0] == "#": 
 781                  continue 
 782   
 783              mol_name = line_split[0] 
 784              mol_name = None 
 785              res_num = int(line_split[1]) 
 786              res_name = line_split[2] 
 787              spin_num = line_split[3] 
 788              spin_num = None 
 789              spin_name = line_split[4] 
 790   
 791              # Create the spin. 
 792              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 793   
 794   
 795 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 796          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 797   
 798          # Reset. 
 799          self.interpreter.reset() 
 800   
 801          # Create the data pipe and load the base data. 
 802          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 803          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 804   
 805          # The model data pipe. 
 806          model = 'NS R1rho 2-site' 
 807          pipe_name = "%s - relax_disp" % model 
 808          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 809          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 810   
 811          # Set the model. 
 812          self.interpreter.relax_disp.select_model(model=model) 
 813   
 814          # Copy the data. 
 815          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 816   
 817          # Alias the spins. 
 818          spin1 = cdp.mol[0].res[0].spin[0] 
 819          spin2 = cdp.mol[0].res[1].spin[0] 
 820   
 821          # The R20 keys. 
 822          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 823          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 824   
 825          # Set the initial parameter values. 
 826          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 827          spin1.pA = 0.779782428085762 
 828          spin1.dw = 7.57855284496424 
 829          spin1.kex = 1116.7911285203 
 830          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 831          spin2.pA = 0.826666229688602 
 832          spin2.dw = 9.5732624231366 
 833          spin2.kex = 1380.46162655657 
 834   
 835          # Test the values when clustering. 
 836          if clustering: 
 837              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 838   
 839          # Low precision optimisation. 
 840          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 841   
 842          # Printout. 
 843          print("\n\nOptimised parameters:\n") 
 844          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 845          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 846          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 847          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 848          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 849          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 850          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 851   
 852   
 853 -    def test_baldwin_synthetic(self): 
 854          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 855   
 856          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 857   
 858          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 859          """ 
 860   
 861          # The path to the data files. 
 862          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 863   
 864          # Create pipe 
 865          pipe_name = 'base pipe' 
 866          pipe_type = 'relax_disp' 
 867          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 868   
 869          # Create base pipe 
 870          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 871   
 872          # Generate the sequence. 
 873          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 874   
 875          # Define the isotope. 
 876          self.interpreter.spin.isotope('1H', spin_id='@H') 
 877   
 878          # Build the experiment IDs. 
 879          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 880          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 881          ids = [] 
 882          for ncyc in ncycs: 
 883              ids.append('CPMG_%s' % ncyc) 
 884   
 885          print("\n\nThe experiment IDs are %s." % ids) 
 886   
 887          # Set up the metadata for the experiments. 
 888          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 889          sfrq = 200. * 1E6 
 890   
 891          # Total time of CPMG block. 
 892          Trelax = 0.04 
 893   
 894          # First set the 
 895          for i in range(len(ids)): 
 896              id = ids[i] 
 897              # Set the spectrometer frequency. 
 898              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 899   
 900              # Set the experiment type. 
 901              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 902   
 903              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 904              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 905   
 906              # Set the relaxation dispersion CPMG frequencies. 
 907              ncyc = ncycs[i] 
 908              nu_cpmg = ncyc / Trelax 
 909              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 910   
 911          # Prepare for R2eff reading. 
 912          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 913          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 914   
 915          # Try reading the R2eff file. 
 916          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 917   
 918          # Check the global data. 
 919          data = [ 
 920              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 921              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 922              ['dispersion_points', len(ncycs)], 
 923              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 924              ['exp_type_list', ['SQ CPMG']], 
 925              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 926              ['spectrometer_frq_count', 1], 
 927              ['spectrometer_frq_list', [sfrq]], 
 928              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 929          ] 
 930          for name, value in data: 
 931              # Does it exist? 
 932              self.assert_(hasattr(cdp, name)) 
 933   
 934              # Check the object. 
 935              obj = getattr(cdp, name) 
 936              if not isinstance(data, dict): 
 937                  self.assertEqual(obj, value) 
 938   
 939              # Check the global dictionary data. 
 940              else: 
 941                  for id in ids: 
 942                      self.assertEqual(obj[id], value[id]) 
 943   
 944          # Check the spin data. 
 945          n_data = [ 
 946              [ 50.000000, 10.367900, 0.1], 
 947              [ 100.000000, 10.146849, 0.1], 
 948              [ 200.000000, 9.765987, 0.1], 
 949              [ 250.000000, 9.409789, 0.1], 
 950              [ 500.000000, 5.829819, 0.1], 
 951              [ 1000.000000, 3.191928, 0.1], 
 952              [ 12500.000000, 2.008231, 0.1] 
 953          ] 
 954          for disp_point, value, error in n_data: 
 955              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 956              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 957              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 958   
 959          # Generate r20 key. 
 960          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 961   
 962          ## Now prepare for MODEL calculation. 
 963          MODEL = "B14" 
 964   
 965          # Change pipe. 
 966          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 967          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 968          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 969   
 970          # Then select model. 
 971          self.interpreter.relax_disp.select_model(model=MODEL) 
 972   
 973          # Store grid and minimisations results. 
 974          grid_results = [] 
 975          mini_results = [] 
 976   
 977          # The grid search size (the number of increments per dimension). 
 978          # If None, use the default values. 
 979          #GRID = None 
 980          GRID = 13 
 981          # Perform Grid Search. 
 982          if GRID: 
 983              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 984              # This speeds it up considerably. 
 985              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 986   
 987              # Then do grid search. 
 988              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 989   
 990              # If no Grid search, set the default values. 
 991          else: 
 992              for param in MODEL_PARAMS[MODEL]: 
 993                  self.interpreter.value.set(param=param, index=None) 
 994                  # Do a grid search, which will store the chi2 value. 
 995              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
 996   
 997          # Store result. 
 998          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
 999              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1000   
1001          ## Now do minimisation. 
1002          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1003          set_func_tol = 1e-10 
1004          set_max_iter = 1000 
1005          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1006   
1007          # Store result. 
1008          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1009              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1010   
1011          # Print results. 
1012          for i in range(len(grid_results)): 
1013              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1014              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1015              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1016              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1017   
1018          # Reference values from Baldwin.py. 
1019          # Exchange rate = k+ + k- (s-1) 
1020          kex = 1000. 
1021          # Fractional population of excited state k+/kex 
1022          pb = 0.01 
1023          # deltaOmega in ppm 
1024          dw_ppm = 2. 
1025          #relaxation rate of ground (s-1) 
1026          R2g = 2. 
1027          #relaxation rate of excited (s-1) 
1028          R2e = 2. 
1029   
1030          # Test the parameters which created the data. 
1031          # This is for the 1H spin. 
1032          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1033   
1034          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1035          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1036          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1037   
1038   
1039 -    def test_baldwin_synthetic_full(self): 
1040          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1041   
1042          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1043          """ 
1044   
1045          # The path to the data files. 
1046          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1047   
1048          # Create pipe 
1049          pipe_name = 'base pipe' 
1050          pipe_type = 'relax_disp' 
1051          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1052   
1053          # Create base pipe 
1054          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1055   
1056          # Generate the sequence. 
1057          # Generate both a 1H spin, and 15N spin. 
1058          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1059   
1060          # Define the isotope. 
1061          self.interpreter.spin.isotope('1H', spin_id='@H') 
1062   
1063          # Build the experiment IDs. 
1064          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1065          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1066          ids = [] 
1067          for ncyc in ncycs: 
1068              ids.append('CPMG_%s' % ncyc) 
1069   
1070          print("\n\nThe experiment IDs are %s." % ids) 
1071   
1072          # Set up the metadata for the experiments. 
1073          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1074          sfrq = 200. * 1E6 
1075   
1076          # Total time of CPMG block. 
1077          Trelax = 0.04 
1078   
1079          # First set the 
1080          for i in range(len(ids)): 
1081              id = ids[i] 
1082              # Set the spectrometer frequency. 
1083              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1084   
1085              # Set the experiment type. 
1086              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1087   
1088              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1089              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1090   
1091              # Set the relaxation dispersion CPMG frequencies. 
1092              ncyc = ncycs[i] 
1093              nu_cpmg = ncyc / Trelax 
1094              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1095   
1096          # Prepare for R2eff reading. 
1097          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1098          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1099   
1100          # Try reading the R2eff file. 
1101          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1102   
1103          # Check the global data. 
1104          data = [ 
1105              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1106              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1107              ['dispersion_points', len(ncycs)], 
1108              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1109              ['exp_type_list', ['SQ CPMG']], 
1110              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1111              ['spectrometer_frq_count', 1], 
1112              ['spectrometer_frq_list', [sfrq]], 
1113              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1114          ] 
1115          for name, value in data: 
1116              # Does it exist? 
1117              self.assert_(hasattr(cdp, name)) 
1118   
1119              # Check the object. 
1120              obj = getattr(cdp, name) 
1121              if not isinstance(data, dict): 
1122                  self.assertEqual(obj, value) 
1123   
1124              # Check the global dictionary data. 
1125              else: 
1126                  for id in ids: 
1127                      self.assertEqual(obj[id], value[id]) 
1128   
1129          # Check the spin data. 
1130          n_data = [ 
1131              [ 50.000000, 10.286255, 0.1], 
1132              [ 100.000000, 10.073083, 0.1], 
1133              [ 200.000000, 9.692746, 0.1], 
1134              [ 250.000000, 9.382441, 0.1], 
1135              [ 500.000000, 6.312396, 0.1], 
1136              [ 1000.000000, 3.957029, 0.1], 
1137              [ 12500.000000, 2.880420, 0.1] 
1138          ] 
1139          for disp_point, value, error in n_data: 
1140              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1141              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1142              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1143   
1144          # Generate r20 key. 
1145          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1146   
1147          ## Now prepare for MODEL calculation. 
1148          MODEL = "B14 full" 
1149   
1150          # Change pipe. 
1151          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1152          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1153          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1154   
1155          # Then select model. 
1156          self.interpreter.relax_disp.select_model(model=MODEL) 
1157   
1158          # Store grid and minimisations results. 
1159          grid_results = [] 
1160          mini_results = [] 
1161          clust_results = [] 
1162   
1163          # The grid search size (the number of increments per dimension). 
1164          # If None, use the default values. 
1165          #GRID = None 
1166          GRID = 13 
1167          # Perform Grid Search. 
1168          if GRID: 
1169              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1170              # This speeds it up considerably. 
1171              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1172   
1173              # Then do grid search. 
1174              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1175   
1176              # If no Grid search, set the default values. 
1177          else: 
1178              for param in MODEL_PARAMS[MODEL]: 
1179                  self.interpreter.value.set(param=param, index=None) 
1180                  # Do a grid search, which will store the chi2 value. 
1181              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1182   
1183          # Store result. 
1184          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1185              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1186   
1187          ## Now do minimisation. 
1188          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1189          set_func_tol = 1e-11 
1190          set_max_iter = 10000 
1191          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1192   
1193          # Store result. 
1194          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1195              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1196   
1197          print("\n# Now print before and after minimisation-\n") 
1198   
1199          # Print results. 
1200          for i in range(len(grid_results)): 
1201              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1202              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1203              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1204              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1205   
1206          # Reference values from Baldwin.py. 
1207          # Exchange rate = k+ + k- (s-1) 
1208          kex = 1000. 
1209          # Fractional population of excited state k+/kex 
1210          pb = 0.01 
1211          # deltaOmega in ppm 
1212          dw_ppm = 2. 
1213          #relaxation rate of ground (s-1) 
1214          R2g = 2. 
1215          #relaxation rate of excited (s-1) 
1216          R2e = 100. 
1217   
1218          # Test the parameters which created the data. 
1219          # This is for the 1H spin. 
1220          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 4) 
1221          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key], R2e, 2) 
1222   
1223          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1224          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1225          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 2) 
1226   
1227   
1228 -    def x_test_bmrb_sub_cpmg(self): 
1229          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1230          This uses CPMG data from: 
1231              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1232                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1233                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1234          """ 
1235   
1236          # Define path to data  
1237          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1238   
1239          # Read data. 
1240          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1241   
1242          # Set element 
1243          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1244          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1245          # Rename molecule from None to 'HEWL' 
1246          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1247          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1248   
1249          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1250              print(spin_id) 
1251              if resn == 'C': 
1252                  print(resi, resn) 
1253   
1254          # Select the thiol state of the system. 
1255          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1256          self.interpreter.bmrb.thiol_state(state='not reported') 
1257   
1258          # relax_data.temp_calibration(ri_id=None, method=None) 
1259   
1260          # Call display of bmrb. 
1261          self.interpreter.bmrb.display() 
1262   
1263   
1264 -    def test_bug_21081_disp_cluster_fail(self): 
1265          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1266   
1267          # Clear the data store. 
1268          self.interpreter.reset() 
1269   
1270          # Load the state. 
1271          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1272          self.interpreter.state.load(state, force=True) 
1273   
1274          # Model selection - to catch the failure. 
1275          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1276   
1277   
1278 -    def test_bug_21460_disp_cluster_fail(self): 
1279          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1280   
1281          # Clear the data store. 
1282          self.interpreter.reset() 
1283   
1284          # Load the state. 
1285          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1286          self.interpreter.state.load(state, force=True) 
1287   
1288          # Execute the auto-analysis (fast). 
1289          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1290          relax_disp.Relax_disp.opt_max_iterations = 1000 
1291          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1292   
1293   
1294 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1295          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1296   
1297          # Clear the data store. 
1298          self.interpreter.reset() 
1299   
1300          # Load the state. 
1301          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1302          self.interpreter.state.load(state, force=True) 
1303   
1304          # Execute the auto-analysis (fast). 
1305          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1306          relax_disp.Relax_disp.opt_max_iterations = 1000 
1307          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1308   
1309   
1310 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1311          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1312   
1313          # Clear the data store. 
1314          self.interpreter.reset() 
1315   
1316          # Load the state. 
1317          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1318          self.interpreter.state.load(state, force=True) 
1319   
1320          # Run the calculation. 
1321          self.interpreter.minimise.calculate(verbosity=1) 
1322   
1323   
1324 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1325          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1326   
1327          # Clear the data store. 
1328          self.interpreter.reset() 
1329   
1330          # Load the state. 
1331          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1332          self.interpreter.state.load(state, force=True) 
1333   
1334          # Execute the auto-analysis (fast). 
1335          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1336          relax_disp.Relax_disp.opt_max_iterations = 1000 
1337          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1338   
1339   
1340 -    def test_bug_21715_clustered_indexerror(self): 
1341          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1342   
1343          # Clear the data store. 
1344          self.interpreter.reset() 
1345   
1346          # Load the state. 
1347          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1348          self.interpreter.state.load(state, force=True) 
1349   
1350          # Execute the auto-analysis (fast). 
1351          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1352          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1353          relax_disp.Relax_disp.opt_max_iterations = 1000 
1354          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=2, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1355   
1356   
1357 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1358          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1359   
1360          # Base data setup. 
1361          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1362   
1363   
1364 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1365          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1366   
1367          # Base data setup. 
1368          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1369   
1370   
1371 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1372          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1373   
1374          # Base data setup. 
1375          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1376   
1377   
1378 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1379          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1380   
1381          # Base data setup. 
1382          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1383   
1384   
1385 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1386          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1387   
1388          # Clear the data store. 
1389          self.interpreter.reset() 
1390   
1391          # Load the state. 
1392          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1393          self.interpreter.state.load(state, force=True) 
1394   
1395          param = 'k_AB' 
1396   
1397          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1398              print(spin_id, spin.params) 
1399              if param in spin.params: 
1400                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1401   
1402          # Perform write. 
1403          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1404   
1405   
1406          # Test the header of the value.write  parameter r2. 
1407          param = 'r2' 
1408          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1409   
1410          file = open(self.tmpdir+sep+'%s.out'%param) 
1411          lines = file.readlines() 
1412          file.close() 
1413   
1414          for i, line in enumerate(lines): 
1415              # Make the string test 
1416              line_split = line.split() 
1417              print(line_split) 
1418   
1419              if len(line_split) > 1: 
1420                  # Break at parameter header. 
1421                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1422                      nr_split_header = len(line_split) 
1423                      nr_split_header_i = i 
1424                      break 
1425   
1426          # Call the line after. 
1427          line_split_val = lines[nr_split_header_i + 1].split() 
1428          print(line_split_val) 
1429   
1430          # Assert that the number of columns is equal, plus 1 for "#". 
1431          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1432   
1433          # Test the header of the value.write for parameter r2eff. 
1434          param = 'r2eff' 
1435          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1436   
1437          file = open(self.tmpdir+sep+'%s.out'%param) 
1438          lines = file.readlines() 
1439          file.close() 
1440   
1441          for i, line in enumerate(lines): 
1442              # Make the string test 
1443              line_split = line.split() 
1444              print(line_split) 
1445   
1446              if len(line_split) > 1: 
1447                  # Break at parameter header. 
1448                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1449                      nr_split_header = len(line_split) 
1450                      nr_split_header_i = i 
1451                      break 
1452   
1453          # Call the line after. 
1454          line_split_val = lines[nr_split_header_i + 1].split() 
1455          print(line_split_val) 
1456   
1457          # Assert that the number of columns is equal, plus 1 for "#". 
1458          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1459   
1460   
1461 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1462          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1463   
1464          # Define path to data  
1465          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1466   
1467          # Read data. 
1468          self.interpreter.results.read(prev_data_path + sep + 'results')         
1469   
1470          # Now count number 
1471          graph_nr = 1 
1472          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1473              print("\nGraph nr %i" % graph_nr) 
1474              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1475                  print(exp_type, frq, offset, point, time) 
1476              graph_nr += 1 
1477   
1478          ## Possibly do an error analysis. 
1479   
1480          # Check if intensity errors have already been calculated by the user. 
1481          precalc = True 
1482          for spin in spin_loop(skip_desel=True): 
1483              # No structure. 
1484              if not hasattr(spin, 'peak_intensity_err'): 
1485                  precalc = False 
1486                  break 
1487   
1488              # Determine if a spectrum ID is missing from the list. 
1489              for id in cdp.spectrum_ids: 
1490                  if id not in spin.peak_intensity_err: 
1491                      precalc = False 
1492                      break 
1493   
1494          # Skip. 
1495          if precalc: 
1496              print("Skipping the error analysis as it has already been performed.") 
1497   
1498          else: 
1499              # Loop over the spectrometer frequencies. 
1500              for frq in loop_frq(): 
1501                  # Generate a list of spectrum IDs matching the frequency. 
1502                  ids = [] 
1503                  for id in cdp.spectrum_ids: 
1504                      # Check that the spectrometer frequency matches. 
1505                      match_frq = True 
1506                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1507                          match_frq = False 
1508   
1509                      # Add the ID. 
1510                      if match_frq: 
1511                          ids.append(id) 
1512   
1513                  # Run the error analysis on the subset. 
1514                  self.interpreter.spectrum.error_analysis(subset=ids) 
1515   
1516          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1517   
1518          model = 'R2eff' 
1519          self.interpreter.relax_disp.select_model(model) 
1520   
1521          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1522              #delattr(spin, 'r2eff') 
1523              #delattr(spin, 'r2eff_err') 
1524              #delattr(spin, 'i0') 
1525              #delattr(spin, 'i0_err') 
1526              setattr(spin, 'r2eff', {}) 
1527              setattr(spin, 'r2eff_err', {}) 
1528              setattr(spin, 'i0', {}) 
1529              setattr(spin, 'i0_err', {}) 
1530   
1531          # Do Grid Search 
1532          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1533   
1534          # Start dic. 
1535          my_dic = {} 
1536   
1537          # Define counter for maximum elements in the numpy array list 
1538          NE = 0 
1539          NS = 1 
1540          NM = 0 
1541          NO = 0 
1542          ND = 0 
1543          NT = 0 
1544   
1545          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1546              # Save to counter. 
1547              if ei > NE: 
1548                  NE = ei 
1549              if mi > NM: 
1550                  NM = mi 
1551              if oi > NO: 
1552                  NO = oi 
1553              if di > ND: 
1554                 ND = di 
1555   
1556              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1557                  # Save to counter. 
1558                  if ti > NT: 
1559                      NT = ti 
1560   
1561          # Add 1 to counter, since index start from 0. 
1562          NE = NE + 1 
1563          NM = NM + 1  
1564          NO = NO + 1 
1565          ND = ND + 1 
1566          NT = NT + 1 
1567   
1568          # Make data array. 
1569          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1570          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1571          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1572          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1573          param_key_list = [] 
1574   
1575   
1576          # Loop over each spectrometer frequency and dispersion point. 
1577          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1578              # Add key to dic. 
1579              my_dic[spin_id] = {} 
1580   
1581              # Generate spin string. 
1582              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1583   
1584              # Loop over the parameters. 
1585              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1586   
1587              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1588                  # Generate the param_key. 
1589                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1590   
1591                  # Append key. 
1592                  param_key_list.append(param_key) 
1593   
1594                  # Add key to dic. 
1595                  my_dic[spin_id][param_key] = {} 
1596   
1597                  # Get the value. 
1598                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1599                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1600   
1601                  # Save to dic. 
1602                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1603                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1604   
1605                  ## Now try do a line of best fit by least squares. 
1606                  # The peak intensities, errors and times. 
1607                  values = [] 
1608                  errors = [] 
1609                  times = [] 
1610                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1611                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1612                      values.append(value) 
1613   
1614                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1615                      errors.append(error) 
1616                      times.append(time) 
1617   
1618                      # Save to numpy arrays. 
1619                      values_arr[ei, 0, mi, oi, di, ti] = value 
1620                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1621                      times_arr[ei, 0, mi, oi, di, ti] = time 
1622                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1623   
1624                  # y= A exp(x * k) 
1625                  # w[i] = ln(y[i]) 
1626                  # int[i] = i0 * exp( - times[i] * r2eff); 
1627                  w = log(array(values)) 
1628                  x = - array(times) 
1629                  n = len(times) 
1630   
1631                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1632                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1633                  R2eff_est = b 
1634                  i0_est = exp(a) 
1635   
1636                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1637                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1638   
1639                  # Print value. 
1640                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1641                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1642   
1643   
1644          # Do minimisation. 
1645          set_func_tol = 1e-25 
1646          set_max_iter = int(1e7) 
1647          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1648   
1649          # Loop over each spectrometer frequency and dispersion point. 
1650          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1651              # Generate spin string. 
1652              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1653   
1654              # Loop over the parameters. 
1655              print("Optimised parameters for spin: %s" % (spin_string)) 
1656   
1657              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1658                  # Generate the param_key. 
1659                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1660   
1661                  # Get the value. 
1662                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1663                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1664   
1665                  # Extract from dic. 
1666                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1667                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1668                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1669                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1670   
1671                  # Print value. 
1672                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1673                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1674   
1675                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1676                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1677   
1678          print(NE, NS, NM, NO, ND, NT) 
1679          for param_key in param_key_list: 
1680              print("        '%s'," % param_key) 
1681          print(values_arr.shape) 
1682   
1683          # Save arrays to profiling. 
1684          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1685          #save(data_path + "values_arr", values_arr) 
1686          #save(data_path + "errors_arr", errors_arr) 
1687          #save(data_path + "times_arr", times_arr) 
1688          #save(data_path + "struct_arr", struct_arr) 
1689   
1690   
1691 -    def test_bug_atul_srivastava(self): 
1692          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1693          shows it is exponential fitting, but only one time point is added per file. 
1694   
1695          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1696          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1697          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1698   
1699          """ 
1700   
1701          # Data path. 
1702          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1703          file = data_path + sep + 'bug_script.py' 
1704   
1705          # Run script. 
1706          self.interpreter.script(file=file, dir=None) 
1707   
1708          # The grid search size (the number of increments per dimension). 
1709          GRID_INC = 11 
1710   
1711          # Check-data. 
1712          ################# 
1713   
1714          # Loop over spins, to see current setup. 
1715          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1716              print(mol_name, resi, resn, spin_id) 
1717   
1718          # Loop over setup. 
1719          for id in cdp.exp_type.keys(): 
1720              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1721   
1722   
1723          # Manual minimisation. 
1724          ################# 
1725          if True: 
1726              # Set the model. 
1727              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1728   
1729              # Check if intensity errors have already been calculated. 
1730              check_intensity_errors() 
1731   
1732              # Calculate the R2eff values for the fixed relaxation time period data types. 
1733              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1734                  self.interpreter.minimise.calculate() 
1735   
1736              # Optimise the model. 
1737              else: 
1738                  constraints = False 
1739                  min_algor = 'Newton' 
1740                  with self.assertRaises(RelaxError): 
1741                      self.interpreter.minimise.grid_search(inc=GRID_INC) 
1742   
1743                  with self.assertRaises(RelaxError): 
1744                      self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
1745          # Inspect. 
1746          if False: 
1747              # Loop over attributes. 
1748              par_attr_list = ['r2eff', 'i0'] 
1749   
1750              # Collect the estimation data. 
1751              my_dic = {} 
1752              param_key_list = [] 
1753              est_keys = [] 
1754              est_key = 'grid' 
1755              est_keys.append(est_key) 
1756              spin_id_list = [] 
1757   
1758              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1759                  # Add key to dic. 
1760                  my_dic[spin_id] = {} 
1761   
1762                  # Add key for estimate. 
1763                  my_dic[spin_id][est_key] = {} 
1764   
1765                  # Add spin key to list. 
1766                  spin_id_list.append(spin_id) 
1767   
1768                  # Generate spin string. 
1769                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1770   
1771                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1772                      # Generate the param_key. 
1773                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1774                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1775   
1776                      # Append key. 
1777                      param_key_list.append(param_key) 
1778   
1779                      # Add key to dic. 
1780                      my_dic[spin_id][est_key][param_key] = {} 
1781   
1782                      # Get the value. 
1783                      # Loop over err attributes. 
1784                      for par_attr in par_attr_list: 
1785                          if hasattr(cur_spin, par_attr): 
1786                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1787                          else: 
1788                              get_par_attr = 0.0 
1789   
1790                          # Save to dic. 
1791                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1792   
1793                      # Check number of values. 
1794                      values = [] 
1795                      errors = [] 
1796                      times = [] 
1797                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1798                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1799                          values.append(value) 
1800   
1801                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1802                          errors.append(error) 
1803                          times.append(time) 
1804   
1805                      # Save to dic. 
1806                      my_dic[spin_id][est_key][param_key]['values'] = values 
1807                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1808                      my_dic[spin_id][est_key][param_key]['times'] = times 
1809   
1810          # Analysis variables. 
1811          ##################### 
1812   
1813          # The dispersion models. 
1814          MODELS = ['R2eff', 'No Rex'] 
1815   
1816          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1817          MC_NUM = 10 
1818   
1819          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1820          MC_SIM_ALL_MODELS = False 
1821   
1822          # The results directory. 
1823          RESULTS_DIR = ds.tmpdir 
1824   
1825          # The directory of results of an earlier analysis without clustering. 
1826          PRE_RUN_DIR = None 
1827   
1828          # The model selection technique to use. 
1829          MODSEL = 'AIC' 
1830   
1831          # The flag for only using numeric models in the final model selection. 
1832          NUMERIC_ONLY = False 
1833   
1834          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1835          INSIGNIFICANCE = 1.0 
1836   
1837          # Auto-analysis execution. 
1838          with self.assertRaises(RelaxError): 
1839              relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1840   
1841   
1842 -    def test_bug_negative_intensities_cpmg(self): 
1843          """Test data, where peak intensities are negative in CPMG 
1844   
1845          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1846          """ 
1847   
1848          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1849   
1850          # Create the spins 
1851          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1852   
1853          # Name the isotope for field strength scaling. 
1854          self.interpreter.spin.isotope(isotope='15N') 
1855   
1856          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1857          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1858   
1859          # Loop over the spectra settings. 
1860          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1861   
1862          # Make empty ncyclist 
1863          ncyclist = [] 
1864   
1865          i = 0 
1866          for line in ncycfile: 
1867              ncyc = line.split()[0] 
1868              time_T2 = float(line.split()[1]) 
1869              vcpmg = line.split()[2] 
1870              set_sfrq = float(line.split()[3]) 
1871              rmsd_err = float(line.split()[4]) 
1872   
1873              # Test if spectrum is a reference 
1874              if float(vcpmg) == 0.0: 
1875                  vcpmg = None 
1876              else: 
1877                  vcpmg = round(float(vcpmg), 3) 
1878   
1879              # Add ncyc to list 
1880              ncyclist.append(int(ncyc)) 
1881   
1882              # Set the current spectrum id 
1883              current_id = "Z_A%s"%(i) 
1884   
1885              # Set the current experiment type. 
1886              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
1887   
1888              # Set the peak intensity errors, as defined as the baseplane RMSD. 
1889              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
1890   
1891              # Set the NMR field strength of the spectrum. 
1892              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
1893   
1894              # Relaxation dispersion CPMG constant time delay T (in s). 
1895              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
1896   
1897              # Set the relaxation dispersion CPMG frequencies. 
1898              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
1899   
1900              i += 1 
1901   
1902          # Specify the duplicated spectra. 
1903          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
1904   
1905          # Delete replicate spectrum 
1906          #self.interpreter.spectrum.delete('Z_A15') 
1907   
1908          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
1909          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
1910   
1911          results_dir = ds.tmpdir 
1912   
1913          # Execute 
1914          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
1915   
1916          # Check spin less R2eff points. 
1917          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
1918              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
1919              if spin_id == ':4@N': 
1920                  self.assertEqual(len(cur_spin.r2eff), 14) 
1921              else: 
1922                  self.assertEqual(len(cur_spin.r2eff), 15) 
1923   
1924   
1925 -    def test_check_missing_r1(self): 
1926          """Test of the check_missing_r1() function.""" 
1927   
1928          # Set up some spins. 
1929          self.setup_missing_r1_spins() 
1930   
1931          # Set variables. 
1932          exp_type = 'R1rho' 
1933          frq = 800.1 * 1E6 
1934   
1935          spectrum_id='test' 
1936   
1937          # Set an experiment type to the pipe. 
1938          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
1939   
1940          # Set a frequency to loop through. 
1941          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
1942   
1943          # Check R1 for DPL94. 
1944          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1945          self.assertEqual(check_missing_r1_return, True) 
1946   
1947          # Check R1 for R2eff. 
1948          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
1949          self.assertEqual(check_missing_r1_return, False) 
1950   
1951          # The path to the data files. 
1952          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
1953   
1954          # Now load some R1 data. 
1955          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
1956   
1957          # Check R1. 
1958          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1959          self.assertEqual(check_missing_r1_return, False) 
1960   
1961   
1962 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
1963          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
1964   
1965          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
1966   
1967          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
1968          """ 
1969   
1970          # Reset. 
1971          #self.interpreter.reset() 
1972   
1973          ## Set Experiments. 
1974          model_create = 'B14' 
1975          #model_create = 'NS CPMG 2-site expanded' 
1976          model_analyse = 'NS CPMG 2-site 3D' 
1977   
1978          # Exp 1 
1979          sfrq_1 = 599.8908617*1E6 
1980          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
1981          time_T2_1 = 0.06 
1982          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
1983          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1984          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1985          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
1986   
1987          sfrq_2 = 499.8908617*1E6 
1988          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
1989          time_T2_2 = 0.05 
1990          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
1991          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1992          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1993          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
1994   
1995          # Collect all exps 
1996          exps = [exp_1, exp_2] 
1997   
1998          spins = [ 
1999              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2000              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2001              ] 
2002   
2003          # Collect the data to be used. 
2004          ds.data = [model_create, model_analyse, spins, exps] 
2005   
2006          # The tmp directory. None is the local directory. 
2007          ds.tmpdir = ds.tmpdir 
2008   
2009          # The results directory. None is the local directory. 
2010          #ds.resdir = None 
2011          ds.resdir = ds.tmpdir 
2012   
2013          # Do r20_from_min_r2eff ?. 
2014          ds.r20_from_min_r2eff = True 
2015   
2016          # Remove insignificant level. 
2017          ds.insignificance = 0.0 
2018   
2019          # The grid search size (the number of increments per dimension). 
2020          ds.GRID_INC = None 
2021   
2022          # The do clustering. 
2023          ds.do_cluster = True 
2024   
2025          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2026          # The default value is 1e-25. 
2027          ds.set_func_tol = 1e-1 
2028   
2029          # The maximum number of iterations. 
2030          # The default value is 1e7. 
2031          ds.set_max_iter = 1000 
2032   
2033          # The verbosity level. 
2034          ds.verbosity = 1 
2035   
2036          # The rel_change WARNING level. 
2037          ds.rel_change = 0.05 
2038   
2039          # The plot_curves. 
2040          ds.plot_curves = False 
2041   
2042          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2043          ds.sherekhan_input = False 
2044   
2045          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2046          ds.opendx = False 
2047   
2048          # The set r2eff err. 
2049          ds.r2eff_err = 0.1 
2050   
2051          # The print result info. 
2052          ds.print_res = True 
2053   
2054          # Execute the script. 
2055          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2056   
2057          cur_spins = ds.data[2] 
2058          # Compare results. 
2059          for i in range(len(cur_spins)): 
2060              res_name, res_num, spin_name, params = cur_spins[i] 
2061              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2062              cur_spin = return_spin(cur_spin_id) 
2063   
2064              grid_params = ds.grid_results[i][3] 
2065   
2066              # Extract the clust results. 
2067              min_params = ds.clust_results[i][3] 
2068              # Now read the parameters. 
2069              print("For spin: '%s'"%cur_spin_id) 
2070              for mo_param in cur_spin.params: 
2071                  # The R2 is a dictionary, depending on spectrometer frequency. 
2072                  if isinstance(getattr(cur_spin, mo_param), dict): 
2073                      grid_r2 = grid_params[mo_param] 
2074                      min_r2 = min_params[mo_param] 
2075                      set_r2 = params[mo_param] 
2076                      for key, val in set_r2.items(): 
2077                          grid_r2_frq = grid_r2[key] 
2078                          min_r2_frq = min_r2[key] 
2079                          set_r2_frq = set_r2[key] 
2080                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2081                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2082                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2083                          if rel_change > ds.rel_change: 
2084                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2085                              print("###################################") 
2086   
2087                          ## Make test on R2. 
2088                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2089                  else: 
2090                      grid_val = grid_params[mo_param] 
2091                      min_val = min_params[mo_param] 
2092                      set_val = params[mo_param] 
2093                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2094                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2095                      if rel_change > ds.rel_change: 
2096                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2097                          print("###################################") 
2098   
2099                      ## Make test on parameters. 
2100                      if mo_param == 'dw': 
2101                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2102                      elif mo_param == 'kex': 
2103                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2104                      elif mo_param == 'pA': 
2105                          self.assertAlmostEqual(set_val, min_val, 2) 
2106   
2107   
2108 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2109          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2110   
2111          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2112   
2113          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2114          """ 
2115   
2116          # Reset. 
2117          #self.interpreter.reset() 
2118   
2119          ## Set Experiments. 
2120          model_create = 'B14' 
2121          #model_create = 'NS CPMG 2-site expanded' 
2122          model_analyse = 'NS CPMG 2-site star' 
2123   
2124          # Exp 1 
2125          sfrq_1 = 599.8908617*1E6 
2126          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2127          time_T2_1 = 0.06 
2128          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2129          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2130          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2131          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2132   
2133          sfrq_2 = 499.8908617*1E6 
2134          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2135          time_T2_2 = 0.05 
2136          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2137          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2138          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2139          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2140   
2141          # Collect all exps 
2142          exps = [exp_1, exp_2] 
2143   
2144          spins = [ 
2145              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2146              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2147              ] 
2148   
2149          # Collect the data to be used. 
2150          ds.data = [model_create, model_analyse, spins, exps] 
2151   
2152          # The tmp directory. None is the local directory. 
2153          ds.tmpdir = ds.tmpdir 
2154   
2155          # The results directory. None is the local directory. 
2156          #ds.resdir = None 
2157          ds.resdir = ds.tmpdir 
2158   
2159          # Do r20_from_min_r2eff ?. 
2160          ds.r20_from_min_r2eff = True 
2161   
2162          # Remove insignificant level. 
2163          ds.insignificance = 0.0 
2164   
2165          # The grid search size (the number of increments per dimension). 
2166          ds.GRID_INC = None 
2167   
2168          # The do clustering. 
2169          ds.do_cluster = True 
2170   
2171          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2172          # The default value is 1e-25. 
2173          ds.set_func_tol = 1e-1 
2174   
2175          # The maximum number of iterations. 
2176          # The default value is 1e7. 
2177          ds.set_max_iter = 1000 
2178   
2179          # The verbosity level. 
2180          ds.verbosity = 1 
2181   
2182          # The rel_change WARNING level. 
2183          ds.rel_change = 0.05 
2184   
2185          # The plot_curves. 
2186          ds.plot_curves = False 
2187   
2188          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2189          ds.sherekhan_input = False 
2190   
2191          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2192          ds.opendx = False 
2193   
2194          # The set r2eff err. 
2195          ds.r2eff_err = 0.1 
2196   
2197          # The print result info. 
2198          ds.print_res = True 
2199   
2200          # Execute the script. 
2201          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2202   
2203          cur_spins = ds.data[2] 
2204          # Compare results. 
2205          for i in range(len(cur_spins)): 
2206              res_name, res_num, spin_name, params = cur_spins[i] 
2207              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2208              cur_spin = return_spin(cur_spin_id) 
2209   
2210              grid_params = ds.grid_results[i][3] 
2211   
2212              # Extract the clust results. 
2213              min_params = ds.clust_results[i][3] 
2214              # Now read the parameters. 
2215              print("For spin: '%s'"%cur_spin_id) 
2216              for mo_param in cur_spin.params: 
2217                  # The R2 is a dictionary, depending on spectrometer frequency. 
2218                  if isinstance(getattr(cur_spin, mo_param), dict): 
2219                      grid_r2 = grid_params[mo_param] 
2220                      min_r2 = min_params[mo_param] 
2221                      set_r2 = params[mo_param] 
2222                      for key, val in set_r2.items(): 
2223                          grid_r2_frq = grid_r2[key] 
2224                          min_r2_frq = min_r2[key] 
2225                          set_r2_frq = set_r2[key] 
2226                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2227                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2228                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2229                          if rel_change > ds.rel_change: 
2230                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2231                              print("###################################") 
2232   
2233                          ## Make test on R2. 
2234                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2235                  else: 
2236                      grid_val = grid_params[mo_param] 
2237                      min_val = min_params[mo_param] 
2238                      set_val = params[mo_param] 
2239                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2240                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2241                      if rel_change > ds.rel_change: 
2242                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2243                          print("###################################") 
2244   
2245                      ## Make test on parameters. 
2246                      if mo_param == 'dw': 
2247                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2248                      elif mo_param == 'kex': 
2249                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2250                      elif mo_param == 'pA': 
2251                          self.assertAlmostEqual(set_val, min_val, 2) 
2252   
2253   
2254 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2255          """Test synthetic cpmg data. 
2256   
2257          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2258          """ 
2259   
2260          # Reset. 
2261          #self.interpreter.reset() 
2262   
2263          ## Set Experiments. 
2264          model_create = 'NS CPMG 2-site 3D' 
2265          #model_create = 'NS CPMG 2-site expanded' 
2266          model_analyse = 'CR72' 
2267          # Exp 1 
2268          sfrq_1 = 599.8908617*1E6 
2269          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2270          time_T2_1 = 0.06 
2271          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2272          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2273          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2274   
2275          sfrq_2 = 499.8908617*1E6 
2276          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2277          time_T2_2 = 0.05 
2278          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2279          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2280          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2281   
2282          # Collect all exps 
2283          exps = [exp_1, exp_2] 
2284   
2285          spins = [ 
2286              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2287              ] 
2288   
2289          # Collect the data to be used. 
2290          ds.data = [model_create, model_analyse, spins, exps] 
2291   
2292          # The tmp directory. None is the local directory. 
2293          ds.tmpdir = ds.tmpdir 
2294   
2295          # The results directory. None is the local directory. 
2296          #ds.resdir = None 
2297          ds.resdir = ds.tmpdir 
2298   
2299          # Do r20_from_min_r2eff ?. 
2300          ds.r20_from_min_r2eff = True 
2301   
2302          # Remove insignificant level. 
2303          ds.insignificance = 0.0 
2304   
2305          # The grid search size (the number of increments per dimension). 
2306          ds.GRID_INC = 8 
2307   
2308          # The do clustering. 
2309          ds.do_cluster = False 
2310   
2311          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2312          # The default value is 1e-25. 
2313          ds.set_func_tol = 1e-9 
2314   
2315          # The maximum number of iterations. 
2316          # The default value is 1e7. 
2317          ds.set_max_iter = 1000 
2318   
2319          # The verbosity level. 
2320          ds.verbosity = 1 
2321   
2322          # The rel_change WARNING level. 
2323          ds.rel_change = 0.05 
2324   
2325          # The plot_curves. 
2326          ds.plot_curves = False 
2327   
2328          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2329          ds.sherekhan_input = False 
2330   
2331          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2332          ds.opendx = False 
2333   
2334          # The set r2eff err. 
2335          ds.r2eff_err = 0.1 
2336   
2337          # The print result info. 
2338          ds.print_res = False 
2339   
2340          # Execute the script. 
2341          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2342   
2343          cur_spins = ds.data[2] 
2344          # Compare results. 
2345          for i in range(len(cur_spins)): 
2346              res_name, res_num, spin_name, params = cur_spins[i] 
2347              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2348              cur_spin = return_spin(cur_spin_id) 
2349   
2350              grid_params = ds.grid_results[i][3] 
2351              min_params = ds.min_results[i][3] 
2352              # Now read the parameters. 
2353              print("For spin: '%s'"%cur_spin_id) 
2354              for mo_param in cur_spin.params: 
2355                  # The R2 is a dictionary, depending on spectrometer frequency. 
2356                  if isinstance(getattr(cur_spin, mo_param), dict): 
2357                      grid_r2 = grid_params[mo_param] 
2358                      min_r2 = min_params[mo_param] 
2359                      set_r2 = params[mo_param] 
2360                      for key, val in set_r2.items(): 
2361                          grid_r2_frq = grid_r2[key] 
2362                          min_r2_frq = min_r2[key] 
2363                          set_r2_frq = set_r2[key] 
2364                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2365                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2366                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2367                          if rel_change > ds.rel_change: 
2368                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2369                              print("###################################") 
2370   
2371                          ## Make test on R2. 
2372                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2373                  else: 
2374                      grid_val = grid_params[mo_param] 
2375                      min_val = min_params[mo_param] 
2376                      set_val = params[mo_param] 
2377                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2378                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2379                      if rel_change > ds.rel_change: 
2380                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2381                          print("###################################") 
2382   
2383                      ## Make test on parameters. 
2384                      if mo_param == 'dw': 
2385                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2386                      elif mo_param == 'kex': 
2387                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2388                      elif mo_param == 'pA': 
2389                          self.assertAlmostEqual(set_val, min_val, 3) 
2390   
2391   
2392 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2393          """Test synthetic cpmg data. 
2394   
2395          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2396          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2397          """ 
2398   
2399          # Reset. 
2400          #self.interpreter.reset() 
2401   
2402          ## Set Experiments. 
2403          model_create = 'NS CPMG 2-site 3D' 
2404          #model_create = 'NS CPMG 2-site expanded' 
2405          model_analyse = 'B14' 
2406          # Exp 1 
2407          sfrq_1 = 599.8908617*1E6 
2408          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2409          time_T2_1 = 0.06 
2410          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2411          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2412          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2413   
2414          sfrq_2 = 499.8908617*1E6 
2415          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2416          time_T2_2 = 0.05 
2417          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2418          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2419          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2420   
2421          # Collect all exps 
2422          exps = [exp_1, exp_2] 
2423   
2424          spins = [ 
2425              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2426              ] 
2427   
2428          # Collect the data to be used. 
2429          ds.data = [model_create, model_analyse, spins, exps] 
2430   
2431          # The tmp directory. None is the local directory. 
2432          ds.tmpdir = ds.tmpdir 
2433   
2434          # The results directory. None is the local directory. 
2435          #ds.resdir = None 
2436          ds.resdir = ds.tmpdir 
2437   
2438          # Do r20_from_min_r2eff ?. 
2439          ds.r20_from_min_r2eff = True 
2440   
2441          # Remove insignificant level. 
2442          ds.insignificance = 0.0 
2443   
2444          # The grid search size (the number of increments per dimension). 
2445          ds.GRID_INC = 8 
2446   
2447          # The do clustering. 
2448          ds.do_cluster = False 
2449   
2450          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2451          # The default value is 1e-25. 
2452          ds.set_func_tol = 1e-9 
2453   
2454          # The maximum number of iterations. 
2455          # The default value is 1e7. 
2456          ds.set_max_iter = 1000 
2457   
2458          # The verbosity level. 
2459          ds.verbosity = 1 
2460   
2461          # The rel_change WARNING level. 
2462          ds.rel_change = 0.05 
2463   
2464          # The plot_curves. 
2465          ds.plot_curves = False 
2466   
2467          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2468          ds.sherekhan_input = False 
2469   
2470          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2471          ds.opendx = False 
2472   
2473          # The set r2eff err. 
2474          ds.r2eff_err = 0.1 
2475   
2476          # The print result info. 
2477          ds.print_res = False 
2478   
2479          # Execute the script. 
2480          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2481   
2482          cur_spins = ds.data[2] 
2483          # Compare results. 
2484          for i in range(len(cur_spins)): 
2485              res_name, res_num, spin_name, params = cur_spins[i] 
2486              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2487              cur_spin = return_spin(cur_spin_id) 
2488   
2489              grid_params = ds.grid_results[i][3] 
2490              min_params = ds.min_results[i][3] 
2491              # Now read the parameters. 
2492              print("For spin: '%s'"%cur_spin_id) 
2493              for mo_param in cur_spin.params: 
2494                  # The R2 is a dictionary, depending on spectrometer frequency. 
2495                  if isinstance(getattr(cur_spin, mo_param), dict): 
2496                      grid_r2 = grid_params[mo_param] 
2497                      min_r2 = min_params[mo_param] 
2498                      set_r2 = params[mo_param] 
2499                      for key, val in set_r2.items(): 
2500                          grid_r2_frq = grid_r2[key] 
2501                          min_r2_frq = min_r2[key] 
2502                          set_r2_frq = set_r2[key] 
2503                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2504                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2505                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2506                          if rel_change > ds.rel_change: 
2507                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2508                              print("###################################") 
2509   
2510                          ## Make test on R2. 
2511                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2512                  else: 
2513                      grid_val = grid_params[mo_param] 
2514                      min_val = min_params[mo_param] 
2515                      set_val = params[mo_param] 
2516                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2517                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2518                      if rel_change > ds.rel_change: 
2519                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2520                          print("###################################") 
2521   
2522                      ## Make test on parameters. 
2523                      if mo_param == 'dw': 
2524                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2525                      elif mo_param == 'kex': 
2526                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2527                      elif mo_param == 'pA': 
2528                          self.assertAlmostEqual(set_val, min_val, 6) 
2529   
2530   
2531 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2532          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2533   
2534          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2535          """ 
2536   
2537          # Reset. 
2538          #self.interpreter.reset() 
2539   
2540          ## Set Experiments. 
2541          model_create = 'NS CPMG 2-site 3D' 
2542          #model_create = 'NS CPMG 2-site expanded' 
2543          model_analyse = 'CR72' 
2544   
2545          # Exp 1 
2546          sfrq_1 = 599.8908617*1E6 
2547          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2548          time_T2_1 = 0.06 
2549          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2550          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2551          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2552          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2553   
2554          sfrq_2 = 499.8908617*1E6 
2555          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2556          time_T2_2 = 0.05 
2557          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2558          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2559          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2560          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2561   
2562          # Collect all exps 
2563          exps = [exp_1, exp_2] 
2564   
2565          spins = [ 
2566              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2567              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2568              ] 
2569   
2570          # Collect the data to be used. 
2571          ds.data = [model_create, model_analyse, spins, exps] 
2572   
2573          # The tmp directory. None is the local directory. 
2574          ds.tmpdir = ds.tmpdir 
2575   
2576          # The results directory. None is the local directory. 
2577          #ds.resdir = None 
2578          ds.resdir = ds.tmpdir 
2579   
2580          # Do r20_from_min_r2eff ?. 
2581          ds.r20_from_min_r2eff = True 
2582   
2583          # Remove insignificant level. 
2584          ds.insignificance = 0.0 
2585   
2586          # The grid search size (the number of increments per dimension). 
2587          ds.GRID_INC = 13 
2588   
2589          # The do clustering. 
2590          ds.do_cluster = True 
2591   
2592          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2593          # The default value is 1e-25. 
2594          ds.set_func_tol = 1e-8 
2595   
2596          # The maximum number of iterations. 
2597          # The default value is 1e7. 
2598          ds.set_max_iter = 10000 
2599   
2600          # The verbosity level. 
2601          ds.verbosity = 1 
2602   
2603          # The rel_change WARNING level. 
2604          ds.rel_change = 0.05 
2605   
2606          # The plot_curves. 
2607          ds.plot_curves = False 
2608   
2609          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2610          ds.sherekhan_input = False 
2611   
2612          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2613          ds.opendx = False 
2614   
2615          # The set r2eff err. 
2616          ds.r2eff_err = 0.1 
2617   
2618          # The print result info. 
2619          ds.print_res = False 
2620   
2621          # Execute the script. 
2622          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2623   
2624          cur_spins = ds.data[2] 
2625          # Compare results. 
2626          for i in range(len(cur_spins)): 
2627              res_name, res_num, spin_name, params = cur_spins[i] 
2628              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2629              cur_spin = return_spin(cur_spin_id) 
2630   
2631              grid_params = ds.grid_results[i][3] 
2632   
2633              # Extract the clust results. 
2634              min_params = ds.clust_results[i][3] 
2635              # Now read the parameters. 
2636              print("For spin: '%s'"%cur_spin_id) 
2637              for mo_param in cur_spin.params: 
2638                  # The R2 is a dictionary, depending on spectrometer frequency. 
2639                  if isinstance(getattr(cur_spin, mo_param), dict): 
2640                      grid_r2 = grid_params[mo_param] 
2641                      min_r2 = min_params[mo_param] 
2642                      set_r2 = params[mo_param] 
2643                      for key, val in set_r2.items(): 
2644                          grid_r2_frq = grid_r2[key] 
2645                          min_r2_frq = min_r2[key] 
2646                          set_r2_frq = set_r2[key] 
2647                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2648                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2649                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2650                          if rel_change > ds.rel_change: 
2651                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2652                              print("###################################") 
2653   
2654                          ## Make test on R2. 
2655                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2656                  else: 
2657                      grid_val = grid_params[mo_param] 
2658                      min_val = min_params[mo_param] 
2659                      set_val = params[mo_param] 
2660                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2661                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2662                      if rel_change > ds.rel_change: 
2663                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2664                          print("###################################") 
2665   
2666                      ## Make test on parameters. 
2667                      if mo_param == 'dw': 
2668                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2669                      elif mo_param == 'kex': 
2670                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2671                      elif mo_param == 'pA': 
2672                          self.assertAlmostEqual(set_val, min_val, 2) 
2673   
2674   
2675 -    def test_cpmg_synthetic_dx_map_points(self): 
2676          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2677   
2678          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2679          """ 
2680   
2681          # Reset. 
2682          #self.interpreter.reset() 
2683   
2684          ## Set Experiments. 
2685          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2686          model_analyse = 'CR72' 
2687          # Exp 1 
2688          sfrq_1 = 599.8908617*1E6 
2689          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2690          time_T2_1 = 0.06 
2691          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2692          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2693          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2694   
2695          sfrq_2 = 499.8908617*1E6 
2696          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2697          time_T2_2 = 0.05 
2698          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2699          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2700          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2701   
2702          # Collect all exps 
2703          exps = [exp_1, exp_2] 
2704   
2705          spins = [ 
2706              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2707              ] 
2708   
2709          # Collect the data to be used. 
2710          ds.data = [model_create, model_analyse, spins, exps] 
2711   
2712          # The tmp directory. None is the local directory. 
2713          ds.tmpdir = ds.tmpdir 
2714   
2715          # The results directory. None is the local directory. 
2716          #ds.resdir = None 
2717          ds.resdir = ds.tmpdir 
2718   
2719          # Do r20_from_min_r2eff ?. 
2720          ds.r20_from_min_r2eff = True 
2721   
2722          # Remove insignificant level. 
2723          ds.insignificance = 0.0 
2724   
2725          # The grid search size (the number of increments per dimension). 
2726          ds.GRID_INC = None 
2727   
2728          # The do clustering. 
2729          ds.do_cluster = False 
2730   
2731          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2732          # The default value is 1e-25. 
2733          ds.set_func_tol = 1e-9 
2734   
2735          # The maximum number of iterations. 
2736          # The default value is 1e7. 
2737          ds.set_max_iter = 1000 
2738   
2739          # The verbosity level. 
2740          ds.verbosity = 1 
2741   
2742          # The rel_change WARNING level. 
2743          ds.rel_change = 0.05 
2744   
2745          # The plot_curves. 
2746          ds.plot_curves = False 
2747   
2748          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2749          ds.sherekhan_input = False 
2750   
2751          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2752          ds.opendx = False 
2753   
2754          # The set r2eff err. 
2755          ds.r2eff_err = 0.1 
2756   
2757          # The print result info. 
2758          ds.print_res = False 
2759   
2760          # Execute the script. 
2761          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2762   
2763          # Get the spins. 
2764          cur_spins = ds.data[2] 
2765   
2766          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2767          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2768          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2769          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2770   
2771          # Copy R2eff, but not the original parameters 
2772          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2773   
2774          # Then select model. 
2775          self.interpreter.relax_disp.select_model(model=model_analyse) 
2776   
2777          # Define dx.map settings. 
2778          ds.dx_inc = 4 
2779          ds.dx_params = ['dw', 'pA', 'kex'] 
2780   
2781          res_name, res_num, spin_name, params = cur_spins[0] 
2782          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2783          cur_spin = return_spin(cur_spin_id) 
2784   
2785          print("Params for dx map is") 
2786          print(ds.dx_params) 
2787          print("Point param for dx map is") 
2788          print(ds.dx_set_val) 
2789          cur_model = model_analyse.replace(' ', '_') 
2790          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2791          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2792          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point) 
2793   
2794          ## Check for file creation 
2795          # Set filepaths. 
2796          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2797          map_net = ds.tmpdir+sep+file_name_map+".net" 
2798          map_general = ds.tmpdir+sep+file_name_map+".general" 
2799   
2800          point_general = ds.tmpdir+sep+file_name_point+".general" 
2801          point_point = ds.tmpdir+sep+file_name_point 
2802   
2803          # Test the files exists. 
2804          self.assert_(access(map_cfg, F_OK)) 
2805          self.assert_(access(map_net, F_OK)) 
2806          self.assert_(access(map_general, F_OK)) 
2807          self.assert_(access(point_general, F_OK)) 
2808          self.assert_(access(point_point, F_OK)) 
2809   
2810          # Open the files for testing. 
2811          # Check the cfg file. 
2812          print("\nChecking the dx map .cfg file.") 
2813          res_file = [ 
2814              '//'+"\n", 
2815              '//'+"\n", 
2816              '// time: Thu May  8 18:55:31 2014'+"\n", 
2817              '//'+"\n", 
2818              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2819              '//'+"\n", 
2820              '//'+"\n", 
2821              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2822              '// title: value = Control Panel'+"\n", 
2823              '//'+"\n", 
2824              '// workspace: width = 251, height = 142'+"\n", 
2825              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2826              '//'+"\n", 
2827              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2828              '// selections: maximum = 2, current = 0 '+"\n", 
2829              '// option[0]: name = "Colour", value = 1'+"\n", 
2830              '// option[1]: name = "Grey", value = 2'+"\n", 
2831              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2832              '// label: value = Colour Selector'+"\n", 
2833              '//'+"\n", 
2834              '// node Image[3]:'+"\n", 
2835              '// title: value = Surface'+"\n", 
2836              '// depth: value = 24'+"\n", 
2837              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2838          ] 
2839          file = open(map_cfg, 'r') 
2840          lines = file.readlines() 
2841          file.close() 
2842          for i in range(len(res_file)): 
2843              # Skip time point 
2844              if i == 2: 
2845                  continue 
2846              self.assertEqual(res_file[i], lines[i]) 
2847   
2848          print("\nChecking the dx map .general file.") 
2849          res_file = [ 
2850              'file = CR72_map_1_N'+"\n", 
2851              'grid = 5 x 5 x 5'+"\n", 
2852              'format = ascii'+"\n", 
2853              'interleaving = field'+"\n", 
2854              'majority = row'+"\n", 
2855              'field = data'+"\n", 
2856              'structure = scalar'+"\n", 
2857              'type = float'+"\n", 
2858              'dependency = positions'+"\n", 
2859              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2860              ''+"\n", 
2861              'end'+"\n", 
2862          ] 
2863          file = open(map_general, 'r') 
2864          lines = file.readlines() 
2865          file.close() 
2866          for i in range(len(res_file)): 
2867              # Skip time point 
2868              #if i == 2: 
2869              #    continue 
2870              self.assertEqual(res_file[i], lines[i]) 
2871   
2872          print("\nChecking the dx point .general file.") 
2873          res_file = [ 
2874              'file = CR72_point_1_N'+"\n", 
2875              'points = 2'+"\n", 
2876              'format = ascii'+"\n", 
2877              'interleaving = field'+"\n", 
2878              'field = locations, field0'+"\n", 
2879              'structure = 3-vector, scalar'+"\n", 
2880              'type = float, float'+"\n", 
2881              ''+"\n", 
2882              'end'+"\n", 
2883          ] 
2884          file = open(point_general, 'r') 
2885          lines = file.readlines() 
2886          file.close() 
2887          for i in range(len(res_file)): 
2888              # Skip time point 
2889              #if i == 2: 
2890              #    continue 
2891              self.assertEqual(res_file[i], lines[i]) 
2892   
2893          print("\nChecking the dx point point file.") 
2894          res_file = [ 
2895              '0.8            3.92           0.39964        1'+"\n", 
2896              '0.76981        3.9169         0.41353        1'+"\n", 
2897          ] 
2898          file = open(point_point, 'r') 
2899          lines = file.readlines() 
2900          file.close() 
2901          for i in range(len(res_file)): 
2902              # Skip time point 
2903              #if i == 2: 
2904              #    continue 
2905              self.assertEqual(res_file[i], lines[i]) 
2906   
2907   
2908 -    def test_curve_type_cpmg_fixed_time(self): 
2909          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
2910   
2911          # Reset. 
2912          self.interpreter.reset() 
2913   
2914          # Load the base data. 
2915          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
2916          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2917   
2918          # The type. 
2919          curve_type = get_curve_type(id='500_133.33.in') 
2920          self.assertEqual(curve_type, 'fixed time') 
2921   
2922   
2923 -    def test_curve_type_r1rho_exponential(self, model=None): 
2924          """Test the curve type detection using the 'M61' exponential test data.""" 
2925   
2926          # Reset. 
2927          self.interpreter.reset() 
2928   
2929          # Load the base data. 
2930          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
2931          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2932   
2933          # The type. 
2934          curve_type = get_curve_type(id='nu_2000_ncyc9') 
2935          self.assertEqual(curve_type, 'exponential') 
2936   
2937   
2938 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
2939          """Test the curve type detection using the 'TP02' fixed time test data.""" 
2940   
2941          # Reset. 
2942          self.interpreter.reset() 
2943   
2944          # Load the base data. 
2945          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
2946          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2947   
2948          # The type. 
2949          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
2950          self.assertEqual(curve_type, 'fixed time') 
2951   
2952   
2953 -    def test_dpl94_data_to_dpl94(self): 
2954          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
2955   
2956          # Fixed time variable. 
2957          ds.fixed = True 
2958   
2959          # Execute the script. 
2960          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
2961   
2962          # The original parameters. 
2963          i0 = [100000.0, 20000.0] 
2964          r1rho_prime = [2.25, 24.0] 
2965          pA = 0.7 
2966          kex = 1000.0 
2967          delta_omega = [1.0, 2.0] 
2968          phi_ex = [] 
2969          for i in range(2): 
2970              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
2971   
2972          # Switch to the 'DPL94' model data pipe, then check for each spin. 
2973          self.interpreter.pipe.switch('DPL94 - relax_disp') 
2974          spin_index = 0 
2975          for spin, spin_id in spin_loop(return_id=True): 
2976              # Printout. 
2977              print("\nSpin %s." % spin_id) 
2978   
2979              # Check the fitted parameters. 
2980              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
2981              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
2982              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
2983   
2984              # Increment the spin index. 
2985              spin_index += 1 
2986   
2987   
2988 -    def test_dx_map_clustered(self): 
2989          """Test making dx_map for residues under clustered calculation. 
2990   
2991          This uses CPMG data from: 
2992              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
2993                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
2994                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
2995          """ 
2996   
2997          # Define path to data  
2998          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
2999   
3000          # Read data. 
3001          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3002   
3003          # Get residue of interest. 
3004          cur_spin_id = ":%i@%s"%(52, 'N') 
3005          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3006   
3007          # Get the spin container. 
3008          cur_spin = return_spin(cur_spin_id) 
3009   
3010          # Get the chi2 value 
3011          pre_chi2 = cur_spin.chi2 
3012   
3013          # Then do a local minimisation. 
3014          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3015          self.interpreter.minimise.calculate() 
3016   
3017          # Get the chi2 value after calculation. 
3018          calc_chi2 = cur_spin.chi2 
3019   
3020          # Assert calculation is equal. 
3021          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3022   
3023          # Define dx.map settings. 
3024          dx_inc = 2 
3025          dx_inc_sides = dx_inc / 2 
3026   
3027          dx_params = ['dw', 'pA', 'kex'] 
3028          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3029   
3030          print("Params for dx map is") 
3031          print(dx_params) 
3032          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3033          print(dx_point_clustered_min) 
3034   
3035          # Define file_names. 
3036          cur_model = 'CR72' 
3037          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3038          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3039   
3040          # Step-size of parameter is 10 % 
3041          param_delta = 0.1 
3042   
3043          # Determine bounds for lower and upper 
3044          lower = [] 
3045          upper = [] 
3046          for i, param_val in enumerate(dx_point_clustered_min): 
3047              param = dx_params[0] 
3048              step_val = param_delta * param_val 
3049              step_length = step_val * dx_inc_sides 
3050   
3051              # Calculate value 
3052              low_val = param_val - step_length 
3053              lower.append(low_val) 
3054   
3055              upp_val = param_val + step_length 
3056              upper.append(upp_val) 
3057   
3058              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3059   
3060          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3061          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3062          dx_param_indexes = dx_inc + 1 
3063          dx_point_index = dx_inc_sides + 1 
3064   
3065          # Find the line number. 
3066          line = 1 
3067          for i in range(1, dx_param_indexes + 1): 
3068              for j in range(1, dx_param_indexes + 1): 
3069                  for k in range(1, dx_param_indexes + 1): 
3070                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3071                          line_chi2 = line 
3072                      # Add to line counter. 
3073                      line += 1 
3074   
3075          # Define temporary folder. 
3076          result_dir = self.tmpdir 
3077   
3078          # For testing. 
3079          #result_dir = None 
3080          #lower = None 
3081          #upper = None 
3082          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3083   
3084   
3085          # Then do the map. 
3086          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3087   
3088          # Print where to locate values. 
3089          nr_chi2_val = dx_param_indexes**3 
3090          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3091          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3092   
3093          ## Check for file creation 
3094          # Set filepaths. 
3095          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3096          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3097          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3098          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3099   
3100          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3101          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3102   
3103          # Test the files exists. 
3104          self.assert_(access(map_cfg, F_OK)) 
3105          self.assert_(access(map_net, F_OK)) 
3106          self.assert_(access(map_general, F_OK)) 
3107          self.assert_(access(point_general, F_OK)) 
3108          self.assert_(access(point_point, F_OK)) 
3109   
3110          # Open the file, and assert the chi2 value is as expected. 
3111          get_data = extract_data(file=map_name) 
3112   
3113          # Extract line 0, column 0. 
3114          test = float(get_data[line_chi2-1][0]) 
3115   
3116          # Assert. 
3117          self.assertAlmostEqual(test, pre_chi2,  6) 
3118   
3119   
3120 -    def test_estimate_r2eff_err(self): 
3121          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3122   
3123          This follows Task 7822. 
3124          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3125   
3126          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3127          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3128          """ 
3129   
3130          # Cluster residues 
3131          cluster_ids = [ 
3132          ":13@N", 
3133          ":15@N", 
3134          ":16@N", 
3135          ":25@N", 
3136          ":26@N", 
3137          ":28@N", 
3138          ":39@N", 
3139          ":40@N", 
3140          ":41@N", 
3141          ":43@N", 
3142          ":44@N", 
3143          ":45@N", 
3144          ":49@N", 
3145          ":52@N", 
3146          ":53@N"] 
3147   
3148          # Load the data. 
3149          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3150   
3151          # The dispersion models. 
3152          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3153   
3154          # The grid search size (the number of increments per dimension). 
3155          GRID_INC = None 
3156   
3157          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3158          MC_NUM = 3 
3159   
3160          # Model selection technique. 
3161          MODSEL = 'AIC' 
3162   
3163          # Execute the auto-analysis (fast). 
3164          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3165          OPT_FUNC_TOL = 1e-25 
3166          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3167          OPT_MAX_ITERATIONS = 10000000 
3168          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3169   
3170          result_dir_name = ds.tmpdir 
3171   
3172          # Make all spins free 
3173          for curspin in cluster_ids: 
3174              self.interpreter.relax_disp.cluster('free spins', curspin) 
3175              # Shut them down 
3176              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3177   
3178          # Select only a subset of spins for global fitting 
3179          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3180          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3181   
3182          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3183          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3184   
3185          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3186          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3187   
3188          # Set the model. 
3189          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3190   
3191          # Check if intensity errors have already been calculated. 
3192          check_intensity_errors() 
3193   
3194          # Do a grid search. 
3195          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3196   
3197          # Minimise. 
3198          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3199   
3200          # Estimate R2eff errors. 
3201          self.interpreter.relax_disp.r2eff_err_estimate() 
3202   
3203          r1_fit = True 
3204   
3205          # Run the analysis. 
3206          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3207   
3208          # Verify the data. 
3209          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3210   
3211   
3212 -    def test_estimate_r2eff_err_auto(self): 
3213          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3214   
3215          This follows Task 7822. 
3216          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3217   
3218          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3219          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3220          """ 
3221   
3222          # Cluster residues 
3223          cluster_ids = [ 
3224          ":13@N", 
3225          ":15@N", 
3226          ":16@N", 
3227          ":25@N", 
3228          ":26@N", 
3229          ":28@N", 
3230          ":39@N", 
3231          ":40@N", 
3232          ":41@N", 
3233          ":43@N", 
3234          ":44@N", 
3235          ":45@N", 
3236          ":49@N", 
3237          ":52@N", 
3238          ":53@N"] 
3239   
3240          # Load the data. 
3241          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3242          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3243   
3244          # Set pipe name, bundle and type. 
3245          pipe_name = 'base pipe' 
3246          pipe_bundle = 'relax_disp' 
3247          pipe_type = 'relax_disp' 
3248   
3249          # Create the data pipe. 
3250          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3251   
3252          file = data_path + '1_setup_r1rho_GUI.py' 
3253          self.interpreter.script(file=file, dir=None) 
3254   
3255          # The dispersion models. 
3256          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3257   
3258          # The grid search size (the number of increments per dimension). 
3259          GRID_INC = None 
3260   
3261          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3262          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3263          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3264          EXP_MC_NUM = -1 
3265   
3266          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3267          MC_NUM = 3 
3268   
3269          # Model selection technique. 
3270          MODSEL = 'AIC' 
3271   
3272          # Execute the auto-analysis (fast). 
3273          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3274          OPT_FUNC_TOL = 1e-25 
3275          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3276          OPT_MAX_ITERATIONS = 10000000 
3277          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3278   
3279          # Make all spins free 
3280          #for curspin in cluster_ids: 
3281          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3282          #    # Shut them down 
3283          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3284   
3285          # Make all spins free 
3286          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3287   
3288          # Select only a subset of spins for global fitting 
3289          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3290          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3291   
3292          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3293          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3294   
3295          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3296          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3297   
3298          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3299              print(spin_id) 
3300   
3301          result_dir_name = self.tmpdir 
3302          r1_fit = True 
3303   
3304          # Run the analysis. 
3305          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3306   
3307          # Verify the data. 
3308          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3309   
3310   
3311 -    def test_estimate_r2eff_err_methods(self): 
3312          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3313          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3314   
3315          This follows Task 7822. 
3316          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3317   
3318          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3319          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3320   
3321          NOTE: The difference in the methods was due to a bug in relax! 
3322          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3323   
3324          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3325          """ 
3326   
3327          # Define data path. 
3328          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3329   
3330          # Create pipe. 
3331          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3332   
3333          # Read results for 2000 MC simulations. 
3334          self.interpreter.results.read(prev_data_path + sep + 'results') 
3335   
3336          # Start dic. 
3337          my_dic = {} 
3338          param_key_list = [] 
3339   
3340          # Do boot strapping ? 
3341          do_boot = True 
3342          if do_boot: 
3343              min_algor = 'Newton' 
3344              min_options = () 
3345              sim_boot = 200 
3346              scaling_list = [1.0, 1.0] 
3347   
3348          # First check sim values. 
3349          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3350              # Add key to dic. 
3351              my_dic[spin_id] = {} 
3352   
3353              # Loop over sim. 
3354              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3355                  # Loop over all exp type. 
3356                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3357                      # Generate the param_key. 
3358                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3359                      r2eff_sim_point = r2eff_sim[param_key] 
3360                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3361   
3362                      # Assert point are higher than 0.0. 
3363                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3364                      #print(point_info) 
3365                      self.assert_(r2eff_sim_point > 0.0) 
3366                      self.assert_(i0_sim_point > 0.0) 
3367   
3368          # Get the data. 
3369          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3370              # Generate spin string. 
3371              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3372   
3373              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3374                  # Generate the param_key. 
3375                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3376   
3377                  # Loop over all sim, and collect data. 
3378                  r2eff_sim_l = [] 
3379                  i0_sim_l = [] 
3380                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3381                      i0_sim = cur_spin.i0_sim[i] 
3382   
3383                      r2eff_sim_i = r2eff_sim[param_key] 
3384                      r2eff_sim_l.append(r2eff_sim_i) 
3385                      i0_sim_i = i0_sim[param_key] 
3386                      i0_sim_l.append(i0_sim_i) 
3387   
3388                  # Take the standard deviation of all values. 
3389                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3390                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3391   
3392                  # Append key. 
3393                  param_key_list.append(param_key) 
3394   
3395                  # Add key to dic. 
3396                  my_dic[spin_id][param_key] = {} 
3397   
3398                  # Get the value. 
3399                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3400                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3401                  i0 = getattr(cur_spin, 'i0')[param_key] 
3402                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3403   
3404                  # Save to dic. 
3405                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3406                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3407                  my_dic[spin_id][param_key]['i0'] = i0 
3408                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3409                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3410                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3411   
3412                  # Assert values are equal 
3413                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3414                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3415   
3416                  if do_boot: 
3417                      values = [] 
3418                      errors = [] 
3419                      times = [] 
3420                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3421                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3422                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3423                          times.append(time) 
3424   
3425                      # Convert to numpy array. 
3426                      values = asarray(values) 
3427                      errors = asarray(errors) 
3428                      times = asarray(times) 
3429   
3430                      R_m_sim_l = [] 
3431                      I0_m_sim_l = [] 
3432                      for j in range(sim_boot): 
3433                          if j in range(0, 100000, 100): 
3434                              print("Simulation %i"%j) 
3435                          # Start minimisation. 
3436   
3437                          # Produce errors 
3438                          I_err = [] 
3439                          for j, error in enumerate(errors): 
3440                              I_error = gauss(values[j], error) 
3441                              I_err.append(I_error) 
3442                          # Convert to numpy array. 
3443                          I_err = asarray(I_err) 
3444   
3445                          x0 = [r2eff, i0] 
3446                          setup(num_params=len(x0), num_times=len(times), values=I_err, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
3447   
3448                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=func, dfunc=dfunc, d2func=d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3449                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3450                          R_m_sim_l.append(R_m_sim_j) 
3451                          I0_m_sim_l.append(I0_m_sim_j) 
3452   
3453                      # Get stats on distribution. 
3454                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3455                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3456                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3457                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3458   
3459   
3460          # A new data pipe. 
3461          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3462          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3463   
3464          # Delete old errors. 
3465          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3466              delattr(cur_spin, 'r2eff_err') 
3467              delattr(cur_spin, 'i0_err') 
3468   
3469          # Set the model. 
3470          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3471   
3472          # Estimate R2eff and errors. 
3473          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3474   
3475          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3476              # Generate spin string. 
3477              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3478   
3479              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3480                  # Generate the param_key. 
3481                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3482   
3483                  # Get the value. 
3484                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3485                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3486                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3487                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3488   
3489                  # Get from dic. 
3490                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3491                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3492                  i0 = my_dic[spin_id][param_key]['i0'] 
3493                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3494                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3495                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3496   
3497                  if do_boot: 
3498                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3499                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3500                  else: 
3501                      r2eff_boot_err = 0.0 
3502                      i0_boot_err = 0.0 
3503   
3504                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3505                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3506                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3507   
3508   
3509          # Now do it manually. 
3510          estimate_r2eff(method='scipy.optimize.leastsq') 
3511   
3512          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3513          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3514   
3515          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3516          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3517   
3518          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3519          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3520   
3521          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3522          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3523   
3524          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3525          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3526   
3527   
3528   
3529 -    def test_exp_fit(self): 
3530          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3531   
3532          # Execute the script. 
3533          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3534   
3535          # The original exponential curve parameters. 
3536          res_data = [ 
3537              [15., 10., 20000., 25000.], 
3538              [12., 11., 50000., 51000.], 
3539              [17., 9., 100000., 96000.] 
3540          ] 
3541   
3542          # List of parameters which do not belong to the model. 
3543          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3544   
3545          # Checks for each residue. 
3546          for i in range(len(res_data)): 
3547              # Printout. 
3548              print("\nResidue number %s." % (i+1)) 
3549   
3550              # Check the fitted parameters. 
3551              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3552              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3553              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3554              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3555   
3556              # Check the simulation errors. 
3557              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3558              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3559              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3560              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3561   
3562              # Check that certain parameters are not present. 
3563              for param in blacklist: 
3564                  print("\tChecking for the absence of the '%s' parameter." % param) 
3565                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3566   
3567          # Check the clustering information. 
3568          self.assert_(hasattr(cdp, 'clustering')) 
3569          keys = ['free spins', 'cluster'] 
3570          for key in keys: 
3571              self.assert_(key in cdp.clustering) 
3572          self.assert_('test' not in cdp.clustering) 
3573          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3574          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3575   
3576   
3577 -    def test_finite_value(self): 
3578          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3579   
3580          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3581          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3582          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3583   
3584          scaling_list = [1.0, 1.0] 
3585          setup(num_params=2, num_times=len(times), values=I, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
3586   
3587          R = - 500. 
3588          I0 = 1000. 
3589          params = [R, I0] 
3590   
3591          chi2 = func(params) 
3592   
3593          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3594          self.assertNotEqual(chi2, inf) 
3595   
3596   
3597 -    def test_hansen_catia_input(self): 
3598          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3599   
3600          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3601          """ 
3602   
3603          # Load the R2eff results file. 
3604          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3605          self.interpreter.results.read(file_name) 
3606          self.interpreter.deselect.spin(':4') 
3607   
3608          # The spin isotopes. 
3609          self.interpreter.spin.isotope("15N") 
3610   
3611          # Generate the input files. 
3612          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3613   
3614          # Check the r2eff set files. 
3615          print("\nChecking the R2eff input set files.") 
3616          files = ['data_set_500.inp', 'data_set_500.inp'] 
3617          for file in files: 
3618              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3619          data_set_500 = [ 
3620              "ID=500\n", 
3621              "Sfrq = 500\n", 
3622              "Temperature = 0.0\n", 
3623              "Nucleus = N15\n", 
3624              "Couplednucleus = H1\n", 
3625              "Time_equil = 0.0\n", 
3626              "Pwx_cp = 0.0\n", 
3627              "Taub = 0.0\n", 
3628              "Time_T2 = 0.03\n", 
3629              "Xcar = 0.0\n", 
3630              "Seqfil = CW_CPMG\n", 
3631              "Minerror = (2.%;0.5/s)\n", 
3632              "Basis = (Iph_7)\n", 
3633              "Format = (0;1;2)\n", 
3634              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3635              "Data = (\n", 
3636              " [70N;spin_70_N_500.cpmg];\n", 
3637              " [71N;spin_71_N_500.cpmg];\n", 
3638              ")\n", 
3639          ] 
3640          file = open(ds.tmpdir+sep+files[0]) 
3641          lines = file.readlines() 
3642          file.close() 
3643          for i in range(len(data_set_500)): 
3644              # Skip the data directory, as this is a random file name. 
3645              if i == 14: 
3646                  continue 
3647   
3648              self.assertEqual(data_set_500[i], lines[i]) 
3649   
3650          # Check the r2eff files. 
3651          print("\nChecking the R2eff input files.") 
3652          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3653          for file in files: 
3654              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3655          spin_70_N_500 = [ 
3656              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3657              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3658              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3659              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3660              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3661              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3662              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3663              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3664              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3665              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3666              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3667              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3668              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3669              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3670              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3671              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3672          ] 
3673          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3674          lines = file.readlines() 
3675          file.close() 
3676          for i in range(len(lines)): 
3677              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3678          for i in range(len(spin_70_N_500)): 
3679              self.assertEqual(spin_70_N_500[i], lines[i]) 
3680   
3681          # Check the main file. 
3682          print("\nChecking the main CATIA execution file.") 
3683          main_file = [ 
3684              "ReadDataset(data_set_500.inp)\n", 
3685              "ReadDataset(data_set_800.inp)\n", 
3686              "ReadParam_Global(ParamGlobal.inp)\n", 
3687              "ReadParam_Local(ParamSet1.inp)\n", 
3688              "\n", 
3689              "FreeLocalParam(all;Omega;false)\n", 
3690              "FreeLocalParam(all;R1iph_500;false)\n", 
3691              "FreeLocalParam(all;R1iph_800;false)\n", 
3692              "\n", 
3693              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3694              "\n", 
3695              "PrintParam(output/GlobalParam.fit;global)\n", 
3696              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3697              "PrintData(output/)\n", 
3698              "\n", 
3699              "ChiSq(all;all)\n", 
3700              "exit(0)\n" 
3701          ] 
3702          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3703          lines = file.readlines() 
3704          file.close() 
3705          for i in range(len(main_file)): 
3706              self.assertEqual(main_file[i], lines[i]) 
3707   
3708   
3709 -    def test_hansen_cpmg_data_auto_analysis(self): 
3710          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3711   
3712          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3713          """ 
3714   
3715          # Set the model. 
3716          ds.models = [ 
3717              MODEL_NOREX, 
3718              MODEL_LM63, 
3719              MODEL_CR72, 
3720              MODEL_IT99 
3721          ] 
3722   
3723          # Execute the script. 
3724          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3725          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3726   
3727          # The R20 keys. 
3728          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3729          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3730   
3731          # The 'No Rex' model checks. 
3732          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3733          spin70 = return_spin(":70") 
3734          spin71 = return_spin(":71") 
3735          print("\n\nOptimised parameters:\n") 
3736          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3737          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3738          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3739          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3740          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3741          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3742          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
3743          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3744          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3745          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
3746   
3747          # The 'LM63' model checks. 
3748          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
3749          spin70 = return_spin(":70") 
3750          spin71 = return_spin(":71") 
3751          print("\n\nOptimised parameters:\n") 
3752          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3753          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3754          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3755          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
3756          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3757          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3758          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
3759          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
3760          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
3761          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
3762          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
3763          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
3764          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
3765          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
3766          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
3767          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
3768   
3769          # The 'CR72' model checks. 
3770          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3771          spin70 = return_spin(":70") 
3772          spin71 = return_spin(":71") 
3773          print("\n\nOptimised parameters:\n") 
3774          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3775          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3776          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3777          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3778          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3779          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3780          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3781          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3782          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3783          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3784          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3785          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3786          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3787          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
3788          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
3789          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
3790          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
3791          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
3792          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
3793   
3794   
3795 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
3796          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3797   
3798          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3799          """ 
3800   
3801          # Set the model and numeric flag. 
3802          ds.models = [ 
3803              MODEL_NOREX, 
3804              MODEL_CR72, 
3805              MODEL_NS_CPMG_2SITE_EXPANDED 
3806          ] 
3807          ds.numeric_only = True 
3808   
3809          # Execute the script. 
3810          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3811   
3812          # The R20 keys. 
3813          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3814          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3815   
3816          # The 'No Rex' model checks. 
3817          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3818          spin70 = return_spin(":70") 
3819          spin71 = return_spin(":71") 
3820          print("\n\nOptimised parameters:\n") 
3821          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3822          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3823          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3824          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3825          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3826          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3827          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
3828          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3829          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3830          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
3831   
3832          # The 'CR72' model checks. 
3833          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3834          spin70 = return_spin(":70") 
3835          spin71 = return_spin(":71") 
3836          print("\n\nOptimised parameters:\n") 
3837          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3838          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3839          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3840          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3841          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3842          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3843          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3844          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3845          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3846          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3847          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3848          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3849          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3850          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
3851          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
3852          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
3853          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
3854          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
3855          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
3856   
3857          # The 'NS CPMG 2-site expanded' model checks. 
3858          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
3859          spin70 = return_spin(":70") 
3860          spin71 = return_spin(":71") 
3861          print("\n\nOptimised parameters:\n") 
3862          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3863          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3864          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3865          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3866          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3867          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3868          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3869          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
3870          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
3871          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
3872          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
3873          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
3874          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
3875          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
3876          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
3877          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
3878          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
3879          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
3880          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
3881   
3882          # The final data pipe checks. 
3883          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
3884          spin70 = return_spin(":70") 
3885          spin71 = return_spin(":71") 
3886          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
3887          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
3888   
3889   
3890 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
3891          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
3892   
3893          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3894          """ 
3895   
3896          # Set the model. 
3897          ds.models = [ 
3898              MODEL_NOREX, 
3899              MODEL_LM63, 
3900              MODEL_CR72, 
3901              MODEL_IT99 
3902          ] 
3903   
3904          # Execute the script. 
3905          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
3906          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
3907   
3908          # The R20 keys. 
3909          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3910          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3911   
3912          # The 'No Rex' model checks. 
3913          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3914          spin70 = return_spin(":70") 
3915          spin71 = return_spin(":71") 
3916          print("\n\nOptimised parameters:\n") 
3917          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3918          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3919          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3920          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3921          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3922          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3923          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
3924          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3925          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3926          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
3927   
3928          # The 'LM63' model checks. 
3929          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
3930          spin70 = return_spin(":70") 
3931          spin71 = return_spin(":71") 
3932          print("\n\nOptimised parameters:\n") 
3933          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3934          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3935          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3936          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
3937          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3938          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3939          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
3940          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
3941          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
3942          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
3943          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
3944          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
3945          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
3946          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
3947          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
3948          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
3949   
3950          # The 'CR72' model checks. 
3951          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3952          spin70 = return_spin(":70") 
3953          spin71 = return_spin(":71") 
3954          print("\n\nOptimised parameters:\n") 
3955          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3956          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3957          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3958          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3959          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3960          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3961          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3962          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3963          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3964          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3965          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3966          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3967          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3968          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
3969          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
3970          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
3971          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
3972          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
3973          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
3974   
3975   
3976 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
3977          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
3978   
3979          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3980          """ 
3981   
3982          # Set the model. 
3983          ds.models = [ 
3984              MODEL_R2EFF, 
3985              MODEL_NOREX, 
3986              MODEL_CR72, 
3987              MODEL_NS_CPMG_2SITE_EXPANDED 
3988          ] 
3989   
3990          # Execute the script. 
3991          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
3992          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3993   
3994          # The R20 keys. 
3995          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3996          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3997   
3998          # The 'No Rex' model checks. 
3999          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4000          spin4 = return_spin(":4") 
4001          spin70 = return_spin(":70") 
4002          spin71 = return_spin(":71") 
4003          print("\n\nOptimised parameters:\n") 
4004          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4005          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4006          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4007          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4008          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4009          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4010          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4011          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4012          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4013          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4014          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4015          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4016   
4017          # The 'CR72' model checks. 
4018          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4019          spin4 = return_spin(":4") 
4020          spin70 = return_spin(":70") 
4021          spin71 = return_spin(":71") 
4022          print("\n\nOptimised parameters:\n") 
4023          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4024          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4025          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4026          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4027          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4028          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4029          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4030          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4031          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4032          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4033          self.assertAlmostEqual(spin4.dw, 0.0, 5) 
4034          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4035          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4036          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4037          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4038          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4039          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4040          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4041          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4042          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4043          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4044          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 3) 
4045          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4046          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4047   
4048   
4049 -    def test_hansen_cpmg_data_to_cr72(self): 
4050          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4051   
4052          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4053          """ 
4054   
4055          # Base data setup. 
4056          self.setup_hansen_cpmg_data(model='CR72') 
4057   
4058          # Alias the spins. 
4059          spin70 = return_spin(":70") 
4060          spin71 = return_spin(":71") 
4061   
4062          # The R20 keys. 
4063          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4064          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4065   
4066          # Set the initial parameter values. 
4067          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4068          spin70.pA = 0.9 
4069          spin70.dw = 6.0 
4070          spin70.kex = 1500.0 
4071          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4072          spin71.pA = 0.9 
4073          spin71.dw = 4.0 
4074          spin71.kex = 1900.0 
4075   
4076          # Low precision optimisation. 
4077          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4078   
4079          # Printout. 
4080          print("\n\nOptimised parameters:\n") 
4081          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4082          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4083          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4084          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4085          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4086          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4087          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4088   
4089          # Checks for residue :70. 
4090          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4091          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4092          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4093          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4094          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4095          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4096   
4097          # Checks for residue :71. 
4098          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4099          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4100          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4101          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4102          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4103   
4104          # Test the conversion to k_AB from kex and pA. 
4105          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4106          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4107   
4108          # Test the conversion to k_BA from kex and pA. 
4109          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4110          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4111   
4112   
4113 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4114          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4115   
4116          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4117          """ 
4118   
4119          # Base data setup. 
4120          self.setup_hansen_cpmg_data(model='CR72 full') 
4121   
4122          # Alias the spins. 
4123          spin70 = return_spin(":70") 
4124          spin71 = return_spin(":71") 
4125   
4126          # The R20 keys. 
4127          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4128          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4129   
4130          # Set the initial parameter values. 
4131          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4132          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4133          spin70.pA = 0.9 
4134          spin70.dw = 6.0 
4135          spin70.kex = 1500.0 
4136          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4137          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4138          spin71.pA = 0.9 
4139          spin71.dw = 4.0 
4140          spin71.kex = 1900.0 
4141   
4142          # Low precision optimisation. 
4143          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4144   
4145          # Printout. 
4146          print("\n\nOptimised parameters:\n") 
4147          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4148          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4149          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4150          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4151          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4152          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4153          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4154          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4155          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4156   
4157          # Checks for residue :70. 
4158          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4159          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4160          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4161          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4162          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4163          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4164          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4165          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4166   
4167          # Checks for residue :71. 
4168          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4169          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4170          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4171          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4172          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4173          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4174   
4175          # Test the conversion to k_AB from kex and pA. 
4176          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4177          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4178   
4179          # Test the conversion to k_BA from kex and pA. 
4180          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4181          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4182   
4183   
4184 -    def test_hansen_cpmg_data_to_it99(self): 
4185          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4186   
4187          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4188          """ 
4189   
4190          # Base data setup. 
4191          self.setup_hansen_cpmg_data(model='IT99') 
4192   
4193          # Alias the spins. 
4194          spin70 = return_spin(":70") 
4195          spin71 = return_spin(":71") 
4196   
4197          # The R20 keys. 
4198          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4199          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4200   
4201          # Set the initial parameter values. 
4202          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4203          spin70.dw = 10.0 
4204          spin70.pA = 0.5 
4205          spin70.tex = 1000.09 
4206          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4207          spin71.dw = 10.0 
4208          spin71.pA = 0.95 
4209          spin71.tex = 0.1 
4210   
4211          # Low precision optimisation. 
4212          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4213   
4214          # Printout. 
4215          print("\n\nOptimised parameters:\n") 
4216          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4217          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4218          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4219          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4220          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4221          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4222          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4223   
4224          # Checks for residue :70. 
4225          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4226          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4227          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4228          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4229          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4230          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4231   
4232          # Checks for residue :71. 
4233          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4234          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4235          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4236          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4237          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4238          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4239   
4240   
4241 -    def test_hansen_cpmg_data_to_lm63(self): 
4242          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4243   
4244          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4245          """ 
4246   
4247          # Base data setup. 
4248          self.setup_hansen_cpmg_data(model='LM63') 
4249   
4250          # Alias the spins. 
4251          spin70 = return_spin(":70") 
4252          spin71 = return_spin(":71") 
4253   
4254          # The R20 keys. 
4255          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4256          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4257   
4258          # Set the initial parameter values. 
4259          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4260          spin70.phi_ex = 0.3 
4261          spin70.kex = 5000.0 
4262          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4263          spin71.phi_ex = 0.1 
4264          spin71.kex = 2500.0 
4265   
4266          # Low precision optimisation. 
4267          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4268   
4269          # Printout. 
4270          print("\n\nOptimised parameters:\n") 
4271          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4272          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4273          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4274          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4275          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4276          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4277   
4278          # Checks for residue :70. 
4279          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4280          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4281          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4282          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4283          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4284   
4285          # Checks for residue :71. 
4286          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4287          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4288          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4289          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4290   
4291   
4292 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4293          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4294   
4295          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4296          """ 
4297   
4298          # Base data setup. 
4299          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4300   
4301          # Alias the spins. 
4302          spin70 = return_spin(":70") 
4303          spin71 = return_spin(":71") 
4304   
4305          # The R20 keys. 
4306          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4307          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4308   
4309          ## Set the initial parameter values. 
4310          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4311          spin70.phi_ex_B = 0.14872003058250227 
4312          spin70.phi_ex_C = 0.1319419923472704 
4313          spin70.kB = 4103.672910444741 
4314          spin70.kC = 7029.001690726248 
4315          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4316          spin71.phi_ex_B = 0.04013553485505605 
4317          spin71.phi_ex_C = 0.020050748406928887 
4318          spin71.kB = 4045.3007136121364 
4319          spin71.kC = 3586.38798270774 
4320   
4321          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4322          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4323   
4324          # Low precision optimisation. 
4325          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4326   
4327          # Printout. 
4328          print("\n\nOptimised parameters:\n") 
4329          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4330          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4331          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4332          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4333          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4334          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4335          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4336          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4337   
4338          # Checks for residue :70. 
4339          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4340          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4341          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4342          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4343          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4344          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4345          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4346   
4347          # Checks for residue :71. 
4348          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4349          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4350          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4351          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4352          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4353          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4354   
4355   
4356 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4357          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4358   
4359          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4360          """ 
4361   
4362          # Base data setup. 
4363          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4364   
4365          # Alias the spins. 
4366          spin70 = return_spin(":70") 
4367          spin71 = return_spin(":71") 
4368   
4369          # The R20 keys. 
4370          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4371          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4372   
4373          # Set the initial parameter values. 
4374          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4375          spin70.pA = 0.9897754407 
4376          spin70.dw = 5.642418428 
4377          spin70.kex = 1743.666375 
4378          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4379          spin71.pA = 0.9968032899 
4380          spin71.dw = 4.577891393 
4381          spin71.kex = 1830.044597 
4382   
4383          # Low precision optimisation. 
4384          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4385   
4386          # Printout. 
4387          print("\n\nOptimised parameters:\n") 
4388          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4389          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4390          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4391          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4392          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4393          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4394          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4395   
4396          # Checks for residue :70. 
4397          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4398          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4399          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4400          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4401          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4402          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4403   
4404          # Checks for residue :71. 
4405          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4406          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4407          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4408          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4409          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4410          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4411   
4412          # Test the conversion to k_AB from kex and pA. 
4413          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4414          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4415   
4416          # Test the conversion to k_BA from kex and pA. 
4417          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4418          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4419   
4420   
4421 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4422          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4423   
4424          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4425          """ 
4426   
4427          # Base data setup. 
4428          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4429   
4430          # Alias the spins. 
4431          spin70 = return_spin(":70") 
4432          spin71 = return_spin(":71") 
4433   
4434          # The R20 keys. 
4435          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4436          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4437   
4438          # Set the initial parameter values. 
4439          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4440          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4441          spin70.pA = 0.9884781357 
4442          spin70.dw = 5.456507396 
4443          spin70.kex = 1906.521189 
4444          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4445          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4446          spin71.pA = 0.986709616684097 
4447          spin71.dw = 2.09245158280905 
4448          spin71.kex = 2438.2766211401 
4449   
4450          # Low precision optimisation. 
4451          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4452   
4453          # Printout. 
4454          print("\n\nOptimised parameters:\n") 
4455          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4456          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4457          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4458          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4459          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4460          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4461          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4462          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4463          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4464   
4465          # Checks for residue :70. 
4466          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4467          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4468          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4469          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4470          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4471          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4472          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4473          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4474   
4475          # Checks for residue :71. 
4476          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4477          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4478          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4479          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4480          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4481          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4482          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4483          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4484   
4485          # Test the conversion to k_AB from kex and pA. 
4486          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4487          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4488   
4489          # Test the conversion to k_BA from kex and pA. 
4490          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4491          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4492   
4493   
4494 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4495          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4496   
4497          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4498          """ 
4499   
4500          # Base data setup. 
4501          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4502   
4503          # Alias the spins. 
4504          spin70 = return_spin(":70") 
4505          spin71 = return_spin(":71") 
4506   
4507          # The R20 keys. 
4508          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4509          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4510   
4511          # Set the initial parameter values. 
4512          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4513          spin70.pA = 0.9 
4514          spin70.dw = 6.0 
4515          spin70.kex = 1500.0 
4516          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4517          spin71.pA = 0.9 
4518          spin71.dw = 4.0 
4519          spin71.kex = 1900.0 
4520   
4521          # Low precision optimisation. 
4522          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4523   
4524          # Printout. 
4525          print("\n\nOptimised parameters:\n") 
4526          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4527          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4528          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4529          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4530          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4531          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4532          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4533   
4534          # Checks for residue :70. 
4535          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4536          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4537          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4538          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4539          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4540          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4541   
4542          # Checks for residue :71. 
4543          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4544          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4545          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4546          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4547          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4548          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4549   
4550          # Test the conversion to k_AB from kex and pA. 
4551          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4552          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4553   
4554          # Test the conversion to k_BA from kex and pA. 
4555          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4556          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4557   
4558   
4559 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4560          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4561   
4562          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4563          """ 
4564   
4565          # Base data setup. 
4566          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4567   
4568          # Alias the spins. 
4569          spin70 = return_spin(":70") 
4570          spin71 = return_spin(":71") 
4571   
4572          # The R20 keys. 
4573          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4574          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4575   
4576          # Set the initial parameter values. 
4577          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4578          spin70.pA = 0.9897519798 
4579          spin70.dw = 5.644862195 
4580          spin70.kex = 1723.820567 
4581          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4582          spin71.pA = 0.9968032899 
4583          spin71.dw = 4.577891393 
4584          spin71.kex = 1830.044597 
4585   
4586          # Low precision optimisation. 
4587          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4588   
4589          # Printout. 
4590          print("\n\nOptimised parameters:\n") 
4591          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4592          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4593          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4594          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4595          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4596          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4597          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4598   
4599          # Checks for residue :70. 
4600          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4601          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4602          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4603          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4604          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4605          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4606   
4607          # Checks for residue :71. 
4608          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4609          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4610          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4611          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4612          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4613   
4614          # Test the conversion to k_AB from kex and pA. 
4615          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4616          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4617   
4618          # Test the conversion to k_BA from kex and pA. 
4619          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4620          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4621   
4622   
4623 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4624          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4625   
4626          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4627          """ 
4628   
4629          # Base data setup. 
4630          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4631   
4632          # Alias the spins. 
4633          spin70 = return_spin(":70") 
4634          spin71 = return_spin(":71") 
4635   
4636          # The R20 keys. 
4637          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4638          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4639   
4640          # Set the initial parameter values. 
4641          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4642          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4643          spin70.pA = 0.987648082613451 
4644          spin70.dw = 5.30679853807572 
4645          spin70.kex = 2033.25380420666 
4646          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4647          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4648          spin71.pA = 0.992258541625787 
4649          spin71.dw = 2.75140650899058 
4650          spin71.kex = 2106.60885247431 
4651   
4652          # Low precision optimisation. 
4653          self.interpreter.minimise.calculate() 
4654   
4655          # Checks for residue :70. 
4656          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4657          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4658   
4659   
4660 -    def test_hansen_cpmgfit_input(self): 
4661          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4662   
4663          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4664          """ 
4665   
4666          # Load the R2eff results file. 
4667          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4668          self.interpreter.results.read(file_name) 
4669          self.interpreter.deselect.spin(':4') 
4670   
4671          # Set up the model. 
4672          self.interpreter.relax_disp.select_model('LM63') 
4673   
4674          # Generate the input files. 
4675          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4676   
4677          # What the files should contain. 
4678          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4679          spin1 = [ 
4680              "title :70@N\n", 
4681              "fields 2 11.7432964915 18.7892743865\n", 
4682              "function CPMG\n", 
4683              "R2 1 10 20\n", 
4684              "Rex 0 100.0 100\n", 
4685              "Tau 0 10.0 100\n", 
4686              "xmgr\n", 
4687              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4688              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4689              "@ xaxis ticklabel format decimal\n", 
4690              "@ yaxis ticklabel format decimal\n", 
4691              "@ xaxis ticklabel char size 0.8\n", 
4692              "@ yaxis ticklabel char size 0.8\n", 
4693              "@ world xmin 0.0\n", 
4694              "data\n", 
4695              "0.133333             16.045541            0.310925             11.743296           \n", 
4696              "0.266667             14.877925            0.303217             11.743296           \n", 
4697              "0.400000             14.357820            0.299894             11.743296           \n", 
4698              "0.533333             12.664495            0.289532             11.743296           \n", 
4699              "0.666667             12.363205            0.287760             11.743296           \n", 
4700              "0.800000             11.092532            0.280514             11.743296           \n", 
4701              "0.933333             10.566090            0.277619             11.743296           \n", 
4702              "1.066667             9.805807             0.273544             11.743296           \n", 
4703              "1.200000             9.564301             0.272276             11.743296           \n", 
4704              "1.333333             9.015634             0.269442             11.743296           \n", 
4705              "1.466667             8.607765             0.267375             11.743296           \n", 
4706              "1.600000             8.279997             0.265740             11.743296           \n", 
4707              "1.733333             8.474536             0.266708             11.743296           \n", 
4708              "1.866667             8.158973             0.265141             11.743296           \n", 
4709              "2.000000             7.988631             0.264304             11.743296           \n", 
4710              "0.133333             22.224914            0.166231             18.789274           \n", 
4711              "0.266667             21.230874            0.162377             18.789274           \n", 
4712              "0.400000             20.603704            0.160017             18.789274           \n", 
4713              "0.533333             20.327797            0.158996             18.789274           \n", 
4714              "0.666667             18.855377            0.153719             18.789274           \n", 
4715              "0.800000             18.537531            0.152617             18.789274           \n", 
4716              "0.933333             17.508069            0.149138             18.789274           \n", 
4717              "1.066667             16.035604            0.144391             18.789274           \n", 
4718              "1.200000             15.168192            0.141717             18.789274           \n", 
4719              "1.333333             14.431802            0.139516             18.789274           \n", 
4720              "1.466667             14.034137            0.138354             18.789274           \n", 
4721              "1.600000             12.920148            0.135192             18.789274           \n", 
4722              "1.733333             12.653673            0.134456             18.789274           \n", 
4723              "1.866667             12.610864            0.134338             18.789274           \n", 
4724              "2.000000             11.969303            0.132601             18.789274           \n" 
4725          ] 
4726          spin2 = [ 
4727              "title :71@N\n", 
4728              "fields 2 11.7432964915 18.7892743865\n", 
4729              "function CPMG\n", 
4730              "R2 1 10 20\n", 
4731              "Rex 0 100.0 100\n", 
4732              "Tau 0 10.0 100\n", 
4733              "xmgr\n", 
4734              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4735              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4736              "@ xaxis ticklabel format decimal\n", 
4737              "@ yaxis ticklabel format decimal\n", 
4738              "@ xaxis ticklabel char size 0.8\n", 
4739              "@ yaxis ticklabel char size 0.8\n", 
4740              "@ world xmin 0.0\n", 
4741              "data\n", 
4742              "0.133333             7.044342             0.170035             11.743296           \n", 
4743              "0.266667             6.781033             0.169228             11.743296           \n", 
4744              "0.400000             6.467623             0.168279             11.743296           \n", 
4745              "0.533333             6.333340             0.167876             11.743296           \n", 
4746              "0.666667             6.323238             0.167846             11.743296           \n", 
4747              "0.800000             6.005245             0.166902             11.743296           \n", 
4748              "0.933333             5.767052             0.166203             11.743296           \n", 
4749              "1.066667             5.476968             0.165361             11.743296           \n", 
4750              "1.200000             5.469949             0.165341             11.743296           \n", 
4751              "1.333333             5.295113             0.164838             11.743296           \n", 
4752              "1.466667             5.435648             0.165242             11.743296           \n", 
4753              "1.600000             5.410400             0.165169             11.743296           \n", 
4754              "1.733333             5.437554             0.165247             11.743296           \n", 
4755              "1.866667             5.176844             0.164501             11.743296           \n", 
4756              "2.000000             5.227232             0.164644             11.743296           \n", 
4757              "0.133333             11.530903            0.081928             18.789274           \n", 
4758              "0.266667             10.983094            0.081041             18.789274           \n", 
4759              "0.400000             10.512403            0.080294             18.789274           \n", 
4760              "0.533333             9.984805             0.079473             18.789274           \n", 
4761              "0.666667             9.573163             0.078845             18.789274           \n", 
4762              "0.800000             9.178810             0.078253             18.789274           \n", 
4763              "0.933333             8.935719             0.077893             18.789274           \n", 
4764              "1.066667             8.610147             0.077416             18.789274           \n", 
4765              "1.200000             8.353778             0.077045             18.789274           \n", 
4766              "1.333333             8.173729             0.076787             18.789274           \n", 
4767              "1.466667             8.091607             0.076670             18.789274           \n", 
4768              "1.600000             7.706420             0.076126             18.789274           \n", 
4769              "1.733333             7.709125             0.076129             18.789274           \n", 
4770              "1.866667             7.610856             0.075992             18.789274           \n", 
4771              "2.000000             7.552584             0.075911             18.789274           \n", 
4772          ] 
4773   
4774          # Check the batch file. 
4775          print("\nChecking the batch file.") 
4776          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
4777          lines = file.readlines() 
4778          file.close() 
4779          for i in range(len(lines)): 
4780              self.assertEqual(batch_file[i], lines[i]) 
4781   
4782          # Check spin :70@N. 
4783          print("\nChecking the spin :70@N input file.") 
4784          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
4785          lines = file.readlines() 
4786          file.close() 
4787          for i in range(len(spin1)): 
4788              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4789          for i in range(len(lines)): 
4790              self.assertEqual(spin1[i], lines[i]) 
4791   
4792          # Check spin :71@N. 
4793          print("\nChecking the spin :71@N input file.") 
4794          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
4795          lines = file.readlines() 
4796          file.close() 
4797          for i in range(len(lines)): 
4798              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4799          for i in range(len(spin2)): 
4800              self.assertEqual(spin2[i], lines[i]) 
4801   
4802   
4803 -    def test_korzhnev_2005_15n_dq_data(self): 
4804          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
4805   
4806          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
4807   
4808          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
4809   
4810              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
4811              - pA = 0.965402506690231, 
4812              - dw = 0.805197170133360, 
4813              - dwH = -0.595536627771890, 
4814              - kex = 569.003663067619868, 
4815              - chi2 = 9.297671357952812. 
4816          """ 
4817   
4818          # Base data setup. 
4819          self.setup_korzhnev_2005_data(data_list=['DQ']) 
4820   
4821          # Alias the spin. 
4822          spin = return_spin(":9@N") 
4823   
4824          # The R20 keys. 
4825          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
4826          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
4827          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
4828   
4829          # Set the initial parameter values. 
4830          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
4831          spin.pA = 0.965638501551899 
4832          spin.dw = 2.8537583461577 
4833          spin.dwH = -0.387633062766635 
4834          spin.kex = 573.704033851592 
4835   
4836          # Low precision optimisation. 
4837          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
4838   
4839          # Monte Carlo simulations. 
4840          self.interpreter.monte_carlo.setup(number=2) 
4841          self.interpreter.monte_carlo.create_data(method='back_calc') 
4842          self.interpreter.monte_carlo.initial_values() 
4843          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
4844          self.interpreter.monte_carlo.error_analysis() 
4845   
4846          # Plot the dispersion curves. 
4847          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
4848   
4849          # Save the results. 
4850          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
4851   
4852          # Printout. 
4853          print("\n\nOptimised parameters:\n") 
4854          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
4855          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
4856          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
4857          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
4858          print("%-20s %20.15g" % ("pA", spin.pA)) 
4859          print("%-20s %20.15g" % ("dw", spin.dw)) 
4860          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
4861          print("%-20s %20.15g" % ("kex", spin.kex)) 
4862          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
4863   
4864          # Checks for residue :9. 
4865          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
4866          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
4867          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
4868          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
4869          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
4870          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
4871          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
4872          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
4873   
4874   
4875 -    def test_korzhnev_2005_15n_mq_data(self): 
4876          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
4877   
4878          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
4879   
4880          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
4881   
4882              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
4883              - pA = 0.930027999814003, 
4884              - dw = 4.338620619954370, 
4885              - dwH = -0.274250775560818, 
4886              - kex = 344.613362916544475, 
4887              - chi2 = 10.367733168217050. 
4888          """ 
4889   
4890          # Base data setup. 
4891          self.setup_korzhnev_2005_data(data_list=['MQ']) 
4892   
4893          # Alias the spin. 
4894          spin = return_spin(":9@N") 
4895   
4896          # The R20 keys. 
4897          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
4898          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
4899          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
4900   
4901          # Set the initial parameter values. 
4902          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
4903          spin.pA = 0.930083249288083 
4904          spin.dw = 4.33890689462363 
4905          spin.dwH = -0.274316585638047 
4906          spin.kex = 344.329651956132 
4907   
4908          # Low precision optimisation. 
4909          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
4910   
4911          # Monte Carlo simulations. 
4912          self.interpreter.monte_carlo.setup(number=2) 
4913          self.interpreter.monte_carlo.create_data(method='back_calc') 
4914          self.interpreter.monte_carlo.initial_values() 
4915          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
4916          self.interpreter.monte_carlo.error_analysis() 
4917   
4918          # Plot the dispersion curves. 
4919          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
4920   
4921          # Save the results. 
4922          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
4923   
4924          # Printout. 
4925          print("\n\nOptimised parameters:\n") 
4926          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
4927          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
4928          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
4929          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
4930          print("%-20s %20.15g" % ("pA", spin.pA)) 
4931          print("%-20s %20.15g" % ("dw", spin.dw)) 
4932          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
4933          print("%-20s %20.15g" % ("kex", spin.kex)) 
4934          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
4935   
4936          # Checks for residue :9. 
4937          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
4938          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
4939          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
4940          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
4941          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
4942          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
4943          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
4944          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
4945   
4946   
4947 -    def test_korzhnev_2005_15n_sq_data(self): 
4948          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
4949   
4950          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
4951   
4952          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
4953   
4954              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
4955              - pA = 0.950003458294991, 
4956              - dw = 4.358402855315123, 
4957              - kex = 429.906473361926999, 
4958              - chi2 = 17.393331915567252. 
4959          """ 
4960   
4961          # Base data setup. 
4962          self.setup_korzhnev_2005_data(data_list=['SQ']) 
4963   
4964          # Alias the spin. 
4965          spin = return_spin(":9@N") 
4966   
4967          # The R20 keys. 
4968          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4969          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
4970          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4971   
4972          # Set the initial parameter values. 
4973          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
4974          spin.pA = 0.950310172115387 
4975          spin.dw = 4.356737157889636 
4976          spin.kex = 433.176323890829849 
4977   
4978          # Low precision optimisation. 
4979          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
4980   
4981          # Monte Carlo simulations. 
4982          self.interpreter.monte_carlo.setup(number=2) 
4983          self.interpreter.monte_carlo.create_data(method='back_calc') 
4984          self.interpreter.monte_carlo.initial_values() 
4985          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
4986          self.interpreter.monte_carlo.error_analysis() 
4987   
4988          # Plot the dispersion curves. 
4989          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
4990   
4991          # Save the results. 
4992          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
4993   
4994          # Printout. 
4995          print("\n\nOptimised parameters:\n") 
4996          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
4997          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
4998          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
4999          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5000          print("%-20s %20.15g" % ("pA", spin.pA)) 
5001          print("%-20s %20.15g" % ("dw", spin.dw)) 
5002          print("%-20s %20.15g" % ("kex", spin.kex)) 
5003          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5004   
5005          # Checks for residue :9. 
5006          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5007          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5008          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5009          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5010          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5011          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5012          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5013   
5014   
5015 -    def test_korzhnev_2005_15n_zq_data(self): 
5016          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5017   
5018          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5019   
5020          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5021   
5022              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5023              - pA = 0.942452612380140, 
5024              - dw = 0.858972784230892, 
5025              - dwH = 0.087155962730608, 
5026              - kex = 373.219151384798920, 
5027              - chi2 = 23.863208106025152. 
5028          """ 
5029   
5030          # Base data setup. 
5031          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5032   
5033          # Alias the spin. 
5034          spin = return_spin(":9@N") 
5035   
5036          # The R20 keys. 
5037          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5038          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5039          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5040   
5041          # Set the initial parameter values. 
5042          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5043          spin.pA = 0.942457332074014 
5044          spin.dw = 0.850592422908884 
5045          spin.dwH = 0.0881272284455416 
5046          spin.kex = 372.745483351305 
5047   
5048          # Low precision optimisation. 
5049          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5050   
5051          # Monte Carlo simulations. 
5052          self.interpreter.monte_carlo.setup(number=2) 
5053          self.interpreter.monte_carlo.create_data(method='back_calc') 
5054          self.interpreter.monte_carlo.initial_values() 
5055          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5056          self.interpreter.monte_carlo.error_analysis() 
5057   
5058          # Plot the dispersion curves. 
5059          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5060   
5061          # Save the results. 
5062          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5063   
5064          # Printout. 
5065          print("\n\nOptimised parameters:\n") 
5066          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5067          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5068          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5069          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5070          print("%-20s %20.15g" % ("pA", spin.pA)) 
5071          print("%-20s %20.15g" % ("dw", spin.dw)) 
5072          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5073          print("%-20s %20.15g" % ("kex", spin.kex)) 
5074          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5075   
5076          # Checks for residue :9. 
5077          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5078          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5079          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5080          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5081          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5082          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5083          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5084          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5085   
5086   
5087 -    def test_korzhnev_2005_1h_mq_data(self): 
5088          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5089   
5090          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5091   
5092          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5093   
5094              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5095              - pA = 0.936911090448340, 
5096              - dw = 4.325314846914845, 
5097              - dwH = -0.213870168665628, 
5098              - kex = 487.361914835074117, 
5099              - chi2 = 14.870371897291138. 
5100          """ 
5101   
5102          # Base data setup. 
5103          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5104   
5105          # Alias the spin. 
5106          spin = return_spin(":9@N") 
5107   
5108          # The R20 keys. 
5109          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5110          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5111          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5112   
5113          # Set the initial parameter values. 
5114          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5115          spin.pA = 0.936884348941701 
5116          spin.dw = 4.326454531583964 
5117          spin.dwH = -0.214026093221782 
5118          spin.kex = 487.043592705469223 
5119   
5120          # Low precision optimisation. 
5121          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5122   
5123          # Monte Carlo simulations. 
5124          self.interpreter.monte_carlo.setup(number=2) 
5125          self.interpreter.monte_carlo.create_data(method='back_calc') 
5126          self.interpreter.monte_carlo.initial_values() 
5127          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5128          self.interpreter.monte_carlo.error_analysis() 
5129   
5130          # Plot the dispersion curves. 
5131          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5132   
5133          # Save the results. 
5134          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5135   
5136          # Printout. 
5137          print("\n\nOptimised parameters:\n") 
5138          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5139          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5140          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5141          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5142          print("%-20s %20.15g" % ("pA", spin.pA)) 
5143          print("%-20s %20.15g" % ("dw", spin.dw)) 
5144          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5145          print("%-20s %20.15g" % ("kex", spin.kex)) 
5146          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5147   
5148          # Checks for residue :9. 
5149          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5150          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5151          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5152          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5153          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5154          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5155          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5156          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5157   
5158   
5159 -    def test_korzhnev_2005_1h_sq_data(self): 
5160          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5161   
5162          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5163   
5164          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5165   
5166              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5167              - pA = 0.946949480545876, 
5168              - dwH = -0.265279672133308, 
5169              - kex = 406.548178869750700, 
5170              - chi2 = 50.400680290545026. 
5171          """ 
5172   
5173          # Base data setup. 
5174          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5175   
5176          # Alias the spin. 
5177          spin = return_spin(":9@N") 
5178   
5179          # The R20 keys. 
5180          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5181          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5182          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5183   
5184          # Set the initial parameter values. 
5185          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5186          spin.pA = 0.946990967372467 
5187          spin.dwH = -0.265308128403529 
5188          spin.kex = 406.843250675648 
5189   
5190          # Low precision optimisation. 
5191          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5192   
5193          # Monte Carlo simulations. 
5194          self.interpreter.monte_carlo.setup(number=2) 
5195          self.interpreter.monte_carlo.create_data(method='back_calc') 
5196          self.interpreter.monte_carlo.initial_values() 
5197          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5198          self.interpreter.monte_carlo.error_analysis() 
5199   
5200          # Plot the dispersion curves. 
5201          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5202   
5203          # Save the results. 
5204          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5205   
5206          # Printout. 
5207          print("\n\nOptimised parameters:\n") 
5208          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5209          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5210          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5211          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5212          print("%-20s %20.15g" % ("pA", spin.pA)) 
5213          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5214          print("%-20s %20.15g" % ("kex", spin.kex)) 
5215          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5216   
5217          # Checks for residue :9. 
5218          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5219          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5220          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5221          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5222          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5223          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5224          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5225   
5226   
5227 -    def test_korzhnev_2005_all_data(self): 
5228          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5229   
5230          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5231   
5232          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5233   
5234              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5235                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5236                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5237                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5238                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5239                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5240              - pA = 0.943125351763911, 
5241              - dw = 4.421827493809807, 
5242              - dwH = -0.272637034755752, 
5243              - kex = 360.609744568697238, 
5244              - chi2 = 162.589570340050813. 
5245          """ 
5246   
5247          # Base data setup. 
5248          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5249   
5250          # Alias the spin. 
5251          spin = return_spin(":9@N") 
5252   
5253          # The R20 keys. 
5254          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5255          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5256          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5257          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5258          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5259          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5260          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5261          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5262          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5263          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5264          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5265          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5266          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5267          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5268          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5269          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5270          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5271          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5272   
5273          # Set the initial parameter values. 
5274          spin.r2 = { 
5275              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5276              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5277              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5278              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5279              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5280              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5281          } 
5282          spin.pA = 0.943129019477673 
5283          spin.dw = 4.42209952545181 
5284          spin.dwH = -0.27258970590969 
5285          spin.kex = 360.516132791038 
5286   
5287          # Low precision optimisation. 
5288          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5289   
5290          # Monte Carlo simulations. 
5291          self.interpreter.monte_carlo.setup(number=2) 
5292          self.interpreter.monte_carlo.create_data(method='back_calc') 
5293          self.interpreter.monte_carlo.initial_values() 
5294          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5295          self.interpreter.monte_carlo.error_analysis() 
5296   
5297          # Plot the dispersion curves. 
5298          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5299   
5300          # Save the results. 
5301          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5302   
5303          # Printout. 
5304          print("\n\nOptimised parameters:\n") 
5305          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5306          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5307          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5308          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5309          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5310          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5311          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5312          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5313          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5314          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5315          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5316          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5317          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5318          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5319          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5320          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5321          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5322          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5323          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5324          print("%-20s %20.15g" % ("pA", spin.pA)) 
5325          print("%-20s %20.15g" % ("dw", spin.dw)) 
5326          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5327          print("%-20s %20.15g" % ("kex", spin.kex)) 
5328          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5329   
5330          # Checks for residue :9. 
5331          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5332          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5333          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5334          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5335          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5336          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5337          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5338          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5339          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5340          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5341          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5342          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5343          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5344          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5345          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5346          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5347          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5348          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5349          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5350          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5351          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5352          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5353          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5354   
5355   
5356 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5357          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5358   
5359          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5360   
5361          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5362   
5363              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5364                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5365                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5366                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5367                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5368                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5369              - pA = 0.943125351763911, 
5370              - dw = 4.421827493809807, 
5371              - dwH = -0.272637034755752, 
5372              - kex = 360.609744568697238, 
5373              - chi2 = 162.589570340050813. 
5374          """ 
5375   
5376          # Base data setup. 
5377          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5378   
5379          # Alias the spin. 
5380          spin = return_spin(":9@N") 
5381   
5382          # The R20 keys. 
5383          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5384          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5385          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5386          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5387          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5388          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5389          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5390          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5391          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5392          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5393          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5394          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5395          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5396          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5397          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5398          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5399          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5400          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5401   
5402          # Set the initial parameter values. 
5403          spin.r2 = { 
5404              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5405              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5406              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5407              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5408              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5409              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5410          } 
5411          spin.pA = 0.943129019477673 
5412          spin.dw = 4.42209952545181 
5413          spin.dwH = -0.27258970590969 
5414          spin.kex = 360.516132791038 
5415   
5416          # Calc the chi2 values at these parameters. 
5417          self.interpreter.minimise.calculate(verbosity=1) 
5418   
5419          # Printout. 
5420          print("\n\nOptimised parameters:\n") 
5421          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5422          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5423          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5424          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5425          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5426          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5427          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5428          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5429          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5430          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5431          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5432          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5433          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5434          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5435          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5436          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5437          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5438          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5439          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5440          print("%-20s %20.15g" % ("pA", spin.pA)) 
5441          print("%-20s %20.15g" % ("dw", spin.dw)) 
5442          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5443          print("%-20s %20.15g" % ("kex", spin.kex)) 
5444          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5445   
5446          # Checks for residue :9. 
5447          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5448   
5449   
5450 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5451          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5452   
5453          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5454   
5455          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5456   
5457            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5458            - 0.483 0.89623903 2.4503699912708878 
5459            - 0.545 1.1694838 
5460            - 0.545 1.1761503 
5461            - 0.622 1.294 
5462            - 0.669 1.5176493 
5463            - 0.722 1.6238791 
5464            - 0.813 1.9395758 
5465            - 1.011 2.3558415 10.547000429321157 
5466          """ 
5467   
5468          # Base data setup. 
5469          model = 'TSMFK01' 
5470          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5471          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5472   
5473          # Alias the spins. 
5474          res61L = cdp.mol[0].res[0].spin[0] 
5475   
5476          # The R20 keys. 
5477          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5478   
5479          # Set the initial parameter values. 
5480          res61L.r2a = {r20_key1: 8.0} 
5481          res61L.dw = 6.5 
5482          res61L.k_AB = 2.5 
5483   
5484          # Low precision optimisation. 
5485          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5486   
5487          # Start testing all possible combinations of graphs. 
5488          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5489          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5490          interpolate_types = [INTERPOLATE_DISP] 
5491   
5492          # Write to temp folder. 
5493          result_dir_name = ds.tmpdir 
5494          result_folders = [model] 
5495          spin_id = ":61@N" 
5496   
5497          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5498          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5499   
5500          for result_folder in result_folders: 
5501              for y_axis in y_axis_types: 
5502                  for x_axis in x_axis_types: 
5503                      for interpolate in interpolate_types: 
5504                          # Determine file name: 
5505                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5506   
5507                          # Make the file name. 
5508                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5509   
5510                          # Write the curves. 
5511                          dir = result_dir_name+sep+result_folder 
5512                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5513                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5514   
5515                          # Get the file path. 
5516                          file_path = get_file_path(file_name, dir) 
5517   
5518                          # Test the plot file exists. 
5519                          print("Testing file access to graph: %s"%file_path) 
5520                          self.assert_(access(file_path, F_OK)) 
5521   
5522                          # Now open, and compare content, line by line. 
5523                          file_prod = open(file_path) 
5524                          lines_prod = file_prod.readlines() 
5525                          file_prod.close() 
5526   
5527                          # Define file to compare against. 
5528                          dir_comp = data_path+sep+result_folder 
5529                          file_path_comp = get_file_path(file_name, dir_comp) 
5530                          file_comp = open(file_path_comp) 
5531                          lines_comp = file_comp.readlines() 
5532                          file_comp.close() 
5533   
5534                          ## Assert number of lines is equal. 
5535                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5536                          for j in range(len(lines_prod)): 
5537                              # Make the string test 
5538                              first_char = lines_prod[j][0] 
5539                              if first_char in ["@", "&"]: 
5540                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5541                              else: 
5542                                  # Split string in x, y, error. 
5543                                  # The error would change per run. 
5544                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5545                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5546                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5547                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5548                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5549   
5550   
5551 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5552          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5553   
5554          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5555          """ 
5556   
5557          # Base data setup. 
5558          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5559   
5560          # Alias the spins. 
5561          res61L = cdp.mol[0].res[0].spin[0] 
5562   
5563          # The R20 keys. 
5564          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5565   
5566          # Set the initial parameter values. 
5567          res61L.r2 = {r20_key1: 8.0} 
5568          res61L.pA = 0.9 
5569          res61L.dw = 6.0 
5570          res61L.kex = 600.0 
5571   
5572          # Low precision optimisation. 
5573          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5574   
5575          # Printout. 
5576          print("\n\nOptimised parameters:\n") 
5577          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5578          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5579          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5580          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5581          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5582          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5583   
5584          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5585          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5586          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5587          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5588          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5589          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5590   
5591          # Test the conversion to k_AB from kex and pA. 
5592          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5593   
5594          # Test the conversion to k_BA from kex and pA. 
5595          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5596   
5597   
5598 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5599          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5600   
5601          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5602          """ 
5603   
5604          # Base data setup. 
5605          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5606   
5607          # Alias the spins. 
5608          res61L = cdp.mol[0].res[0].spin[0] 
5609   
5610          # The R20 keys. 
5611          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5612   
5613          # Set the initial parameter values. 
5614          res61L.r2a = {r20_key1: 8.0} 
5615          res61L.r2b = {r20_key1: 105.0} 
5616          res61L.pA = 0.9 
5617          res61L.dw = 6.0 
5618          res61L.kex = 500.0 
5619   
5620          # Low precision optimisation. 
5621          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5622   
5623          # Printout. 
5624          print("\n\nOptimised parameters:\n") 
5625          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5626          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5627          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5628          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5629          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5630          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5631          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5632   
5633          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5634          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5635          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5636          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5637          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5638          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5639          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5640   
5641   
5642 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5643          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5644   
5645          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5646   
5647          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5648   
5649            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5650            - 0.483 0.89623903 2.4503699912708878 
5651            - 0.545 1.1694838 
5652            - 0.545 1.1761503 
5653            - 0.622 1.294 
5654            - 0.669 1.5176493 
5655            - 0.722 1.6238791 
5656            - 0.813 1.9395758 
5657            - 1.011 2.3558415 10.547000429321157 
5658          """ 
5659   
5660          # Base data setup. 
5661          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5662   
5663          # Alias the spins. 
5664          res61L = cdp.mol[0].res[0].spin[0] 
5665   
5666          # The R20 keys. 
5667          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5668   
5669          # Set the initial parameter values. 
5670          res61L.r2a = {r20_key1: 8.0} 
5671          res61L.dw = 6.5 
5672          res61L.k_AB = 2.5 
5673   
5674          # Low precision optimisation. 
5675          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5676   
5677          # Printout. 
5678          print("\n\nOptimised parameters:\n") 
5679          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5680          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5681          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5682          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5683          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5684   
5685          # Checks for residue :61. Reference values from paper 
5686   
5687          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5688   
5689   
5690 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5691          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5692   
5693          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5694   
5695          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5696   
5697          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5698   
5699            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5700              - k_AB = 11.3 +/- 0.7 s^-1, 
5701              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5702              - R2 = 8.0 +/- 0.5 s^-1. 
5703   
5704            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5705              - k_AB = 10.55 +/- 0.08 s^-1, 
5706              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5707              - R2 = 8.4 +/- 0.3 s^-1. 
5708   
5709          Conversion of paper results to relax results is performed by: 
5710   
5711            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5712   
5713          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5714   
5715            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5716            - 0.483 0.89623903 2.4503699912708878 
5717            - 0.545 1.1694838 
5718            - 0.545 1.1761503 
5719            - 0.622 1.294 
5720            - 0.669 1.5176493 
5721            - 0.722 1.6238791 
5722            - 0.813 1.9395758 
5723            - 1.011 2.3558415 10.547000429321157 
5724          """ 
5725   
5726          # Base data setup. 
5727          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5728   
5729          # Alias the spins. 
5730          res61L = cdp.mol[0].res[0].spin[0] 
5731   
5732          # The R20 keys. 
5733          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
5734   
5735          # Set the initial parameter values. 
5736          res61L.r2a = {r20_key1: 8.0} 
5737          res61L.dw = 6.5 
5738          res61L.k_AB = 11.0 
5739   
5740          # Low precision optimisation. 
5741          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5742   
5743          # Printout. 
5744          print("\n\nOptimised parameters:\n") 
5745          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5746          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5747          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5748          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5749          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5750   
5751          # Checks for residue :61. Reference values from paper 
5752   
5753          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
5754          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
5755          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
5756   
5757   
5758 -    def test_lm63_3site_synthetic(self): 
5759          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
5760   
5761          # The path to the data files. 
5762          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
5763   
5764          # Load the state file. 
5765          self.interpreter.reset() 
5766          self.interpreter.state.load(data_path+sep+'r2eff_values') 
5767   
5768          # A new data pipe. 
5769          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
5770          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
5771   
5772          # Set up the model data. 
5773          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
5774          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
5775          self.interpreter.spin.isotope('15N') 
5776   
5777          # Alias the spins. 
5778          spin1 = return_spin(":1") 
5779          spin2 = return_spin(":2") 
5780   
5781          # The R20 keys. 
5782          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5783          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5784   
5785          # Manually set the parameter values. 
5786          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
5787          spin1.phi_ex_B = 0.1 
5788          spin1.phi_ex_C = 0.5 
5789          spin1.kB = 1500.0 
5790          spin1.kC = 2500.0 
5791          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
5792          spin2.phi_ex_B = 0.1 
5793          spin2.phi_ex_C = 0.5 
5794          spin2.kB = 1500.0 
5795          spin2.kC = 2500.0 
5796   
5797          # Low precision optimisation. 
5798          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5799   
5800          # Monte Carlo simulations. 
5801          self.interpreter.monte_carlo.setup(number=3) 
5802          self.interpreter.monte_carlo.create_data(method='back_calc') 
5803          self.interpreter.monte_carlo.initial_values() 
5804          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
5805          self.interpreter.monte_carlo.error_analysis() 
5806   
5807          # Save the results. 
5808          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
5809   
5810          # The model checks. 
5811          print("\n\nOptimised parameters:\n") 
5812          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
5813          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
5814          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
5815          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
5816          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
5817          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
5818          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
5819          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
5820          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
5821          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
5822          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5823          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5824          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5825          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5826          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
5827          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
5828          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
5829          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5830          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5831          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5832          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5833          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
5834   
5835   
5836 -    def test_m61_data_to_m61(self): 
5837          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
5838   
5839          # Fixed time variable. 
5840          ds.fixed = True 
5841   
5842          # Execute the script. 
5843          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
5844   
5845          # The original parameters. 
5846          i0 = [100000.0, 20000.0] 
5847          r1rho_prime = [2.25, 24.0] 
5848          pA = 0.7 
5849          kex = 1000.0 
5850          delta_omega = [1.0, 2.0] 
5851          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
5852          phi_ex = [] 
5853          for i in range(2): 
5854              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
5855          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
5856   
5857          # Switch to the 'R2eff' model data pipe, then check for each spin. 
5858          self.interpreter.pipe.switch('R2eff - relax_disp') 
5859          spin_index = 0 
5860          for spin, spin_id in spin_loop(return_id=True): 
5861              # Printout. 
5862              print("\nSpin %s." % spin_id) 
5863   
5864              # Check the fitted parameters. 
5865              for i in range(len(keys)): 
5866                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
5867   
5868              # Increment the spin index. 
5869              spin_index += 1 
5870   
5871          # The R20 keys. 
5872          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
5873   
5874          # Switch to the 'M61' model data pipe, then check for each spin. 
5875          self.interpreter.pipe.switch('M61 - relax_disp') 
5876          spin_index = 0 
5877          for spin, spin_id in spin_loop(return_id=True): 
5878              # Printout. 
5879              print("\nSpin %s." % spin_id) 
5880   
5881              # Check the fitted parameters. 
5882              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
5883              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
5884              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
5885   
5886              # Increment the spin index. 
5887              spin_index += 1 
5888   
5889   
5890 -    def test_m61_exp_data_to_m61(self): 
5891          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
5892   
5893          # Fixed time variable. 
5894          ds.fixed = False 
5895   
5896          # Single spin optimisation. 
5897          ds.single = True 
5898   
5899          # Execute the script. 
5900          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
5901   
5902          # The original parameters. 
5903          i0 = [100000.0, 20000.0] 
5904          r1rho_prime = [2.25, 24.0] 
5905          pA = 0.7 
5906          kex = 1000.0 
5907          delta_omega = [1.0, 2.0] 
5908          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
5909          phi_ex = [] 
5910          for i in range(2): 
5911              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
5912          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
5913   
5914          # Switch to the 'R2eff' model data pipe, then check for each spin. 
5915          self.interpreter.pipe.switch('R2eff - relax_disp') 
5916          spin_index = 0 
5917          for spin, spin_id in spin_loop(return_id=True): 
5918              # Printout. 
5919              print("\nSpin %s." % spin_id) 
5920   
5921              # Check the fitted parameters. 
5922              for i in range(len(keys)): 
5923                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
5924   
5925              # Increment the spin index. 
5926              spin_index += 1 
5927   
5928          # The R20 keys. 
5929          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
5930   
5931          # Switch to the 'M61' model data pipe, then check for each spin. 
5932          self.interpreter.pipe.switch('M61 - relax_disp') 
5933          spin_index = 0 
5934          for spin, spin_id in spin_loop(return_id=True): 
5935              # Printout. 
5936              print("\nSpin %s." % spin_id) 
5937   
5938              # Check the fitted parameters. 
5939              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
5940              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
5941              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
5942   
5943              # Increment the spin index. 
5944              spin_index += 1 
5945   
5946   
5947 -    def test_m61b_data_to_m61b(self): 
5948          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
5949   
5950          # Execute the script. 
5951          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
5952   
5953          # The original parameters. 
5954          i0 = [100000.0, 20000.0] 
5955          r1rho_prime = [10.0, 24.0] 
5956          pA = 0.95 
5957          kex = 2000.0 
5958          delta_omega = [1.0, 2.0] 
5959   
5960          # The R20 keys. 
5961          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
5962   
5963          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
5964          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
5965          spin_index = 0 
5966          for spin, spin_id in spin_loop(return_id=True): 
5967              # Printout. 
5968              print("\nSpin %s." % spin_id) 
5969   
5970              # Check the fitted parameters. 
5971              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
5972              self.assertAlmostEqual(spin.pA, pA, 2) 
5973              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
5974              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
5975   
5976              # Increment the spin index. 
5977              spin_index += 1 
5978   
5979   
5980 -    def test_model_nesting_and_param(self): 
5981          """Test that all models which can nest, have all their parameters converted.""" 
5982   
5983          # Set the experiment type. 
5984          cdp.exp_type_list = EXP_TYPE_LIST 
5985   
5986          # Get info for all models. 
5987          all_models_info = models_info(models=MODEL_LIST_FULL) 
5988   
5989          # Loop over all models. 
5990          print("Printing the listed of nested models for each model.") 
5991          print("#########################################") 
5992          for model_info in all_models_info: 
5993              print("%s"%model_info.model), 
5994              print("<-"), 
5995              nest_list = model_info.nest_list 
5996              if nest_list == None: 
5997                  nest_list = ["None"] 
5998              print(', '.join(map(str, nest_list))) 
5999   
6000              # Skip if there is no model to nest from. 
6001              if nest_list == ["None"]: 
6002                  continue 
6003   
6004              # Assign params to variable. 
6005              model_params = model_info.params 
6006   
6007              # Now loop over the nested models. 
6008              for nested_model in nest_list: 
6009                  # Get the params for the nested model. 
6010                  nested_model_params = MODEL_PARAMS[nested_model] 
6011   
6012                  # Get the dictionary of parameter conversion. 
6013                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6014   
6015                  # Test the number of elements in the dictionary. 
6016                  self.assertEqual(len(par_dic), len(model_params)) 
6017   
6018                  # Loop over dictionary. 
6019                  for param, param_conv in par_dic.iteritems(): 
6020                          if param != param_conv: 
6021                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, param_conv, param)) 
6022                          self.assertNotEqual(param_conv, None) 
6023   
6024   
6025 -    def test_ns_mmq_3site(self): 
6026          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6027   
6028          # Execute the script. 
6029          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6030   
6031          # Check the chi-squared value. 
6032          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6033   
6034   
6035 -    def test_ns_mmq_3site_linear(self): 
6036          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6037   
6038          # Execute the script. 
6039          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6040   
6041          # Check the chi-squared value. 
6042          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6043   
6044   
6045 -    def test_ns_r1rho_3site(self): 
6046          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6047   
6048          # Execute the script. 
6049          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6050   
6051          # Check the chi-squared value. 
6052          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6053   
6054   
6055 -    def test_ns_r1rho_3site_linear(self): 
6056          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6057   
6058          # Execute the script. 
6059          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6060   
6061          # Check the chi-squared value. 
6062          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6063   
6064   
6065 -    def test_repeat_cpmg(self): 
6066          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6067   
6068          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6069          """ 
6070   
6071          # Reset. 
6072          self.interpreter.reset() 
6073   
6074          # Define base path to files. 
6075          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6076   
6077          # Setup dictionary with settings. 
6078          sdic = {} 
6079           
6080          # Spectrometer frqs in list. 
6081          sfrq_1 = 499.86214 
6082          sfrq_2 = 599.8908587 
6083          sfrqs = [sfrq_1, sfrq_2] 
6084           
6085          # Store in dictionary. 
6086          sdic['sfrqs'] = sfrqs 
6087           
6088          # Store unit for frq. 
6089          sdic['sfrq_unit'] = 'MHz' 
6090           
6091          # Store exp_type 
6092          sdic['exp_type'] = 'SQ CPMG' 
6093   
6094          # Store spin isotope 
6095          sdic['isotope'] = '15N' 
6096   
6097          # How intensity was measured. 
6098          sdic['int_method'] = 'height' 
6099   
6100          # Define the time for result directory. 
6101          sdic['time'] = '2014_09' 
6102   
6103          # Initialize frq dics. 
6104          for frq in sfrqs: 
6105              key = DIC_KEY_FORMAT % (frq) 
6106              sdic[key] = {} 
6107           
6108          # Set keys. 
6109          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6110          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6111           
6112          # Store time T2. 
6113          sdic[e_1]['time_T2'] = 0.04 
6114          sdic[e_2]['time_T2'] = 0.06 
6115           
6116          # Set ncyc. 
6117          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6118          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6119   
6120          # Calculate the cpmg_frq and store. 
6121          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6122          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6123           
6124          # Define peak lists. 
6125          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6126          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6127          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6128          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6129           
6130          # Define folder to all rmsd files. 
6131          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6132          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6133          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6134          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6135   
6136          # Define temporary folder. 
6137          sdic['results_dir'] = self.tmpdir 
6138   
6139          # Setup class with data. 
6140          RDR =  Relax_disp_rep(sdic) 
6141   
6142          # Setup base information. 
6143          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6144   
6145          methods = ['FT', 'MDD'] 
6146          #methods = ['FT'] 
6147   
6148          # Set the intensity. 
6149          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6150          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6151   
6152          # Try plot some intensity correlations. 
6153          if True: 
6154              selection = None 
6155   
6156              # Now make a spin selection. 
6157              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6158   
6159              # For mdd 
6160              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6161   
6162              # Plot correlation of intensity 
6163              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6164              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6165              corr_data = [fig1, fig2] 
6166   
6167              write_stats = True 
6168              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6169   
6170              # Open stat file. 
6171              if write_stats: 
6172                  for i, corr_data_i in enumerate(corr_data): 
6173                      data, methods, glob_inis = corr_data[i] 
6174                      data_x, data_y = data 
6175                      method_x, method_y = methods 
6176                      glob_ini_x, glob_ini_y = glob_inis 
6177                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6178                      np = len(x) 
6179   
6180                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6181   
6182                      if selection == None: 
6183                          file_name = file_name_ini + '_all.txt' 
6184                      else: 
6185                          file_name = file_name_ini + '_sel.txt' 
6186                      path = RDR.results_dir 
6187                      data = extract_data(file=file_name, dir=path) 
6188   
6189                      # Loop over the lines. 
6190                      for i, data_i in enumerate(data): 
6191                          print(i, data_i) 
6192   
6193   
6194          # Try plot some intensity statistics. 
6195          if True: 
6196              # Collect r2eff values. 
6197              selections = [None, ':2,3'] 
6198              for selection in selections: 
6199                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6200                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6201   
6202                  # Get R2eff stats. 
6203                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6204   
6205                  ## Plot R2eff stats 
6206                  write_stats = True 
6207                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6208   
6209                  # Open stat file. 
6210                  if write_stats: 
6211                      if selection == None: 
6212                          file_name = 'int_stat_all.txt' 
6213                      else: 
6214                          file_name = 'int_stat_sel.txt' 
6215                      path = RDR.results_dir 
6216                      data = extract_data(file=file_name, dir=path) 
6217   
6218                      # Loop over the lines. 
6219                      for i, data_i in enumerate(data): 
6220                          print(i, data_i) 
6221   
6222   
6223          # Try write some R2eff correlations. 
6224          if True: 
6225              selection = None 
6226              # Collect r2eff values. 
6227              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6228   
6229              # For all spins, mdd 
6230              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6231   
6232              # Plot correlation of intensity 
6233              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6234              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6235              corr_data = [fig1, fig2] 
6236   
6237              write_stats = True 
6238              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6239   
6240              # Open stat file. 
6241              if write_stats: 
6242                  for i, corr_data_i in enumerate(corr_data): 
6243                      data, methods, glob_inis = corr_data[i] 
6244                      data_x, data_y = data 
6245                      method_x, method_y = methods 
6246                      glob_ini_x, glob_ini_y = glob_inis 
6247                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6248                      np = len(x) 
6249   
6250                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6251   
6252                      if selection == None: 
6253                          file_name = file_name_ini + '_all.txt' 
6254                      else: 
6255                          file_name = file_name_ini + '_sel.txt' 
6256                      path = RDR.results_dir 
6257                      data = extract_data(file=file_name, dir=path) 
6258   
6259                      # Loop over the lines. 
6260                      for i, data_i in enumerate(data): 
6261                          print(i, data_i) 
6262   
6263   
6264          # Try plot some R2eff statistics. 
6265          if True: 
6266              # Collect r2eff values. 
6267              selections = [None, ':2,3'] 
6268              for selection in selections: 
6269                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6270                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6271   
6272                  # Get R2eff stats. 
6273                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6274   
6275                  ## Plot R2eff stats 
6276                  write_stats = True 
6277                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6278   
6279                  # Open stat file. 
6280                  if write_stats: 
6281                      if selection == None: 
6282                          file_name = 'r2eff_stat_all.txt' 
6283                      else: 
6284                          file_name = 'r2eff_stat_sel.txt' 
6285                      path = RDR.results_dir 
6286                      data = extract_data(file=file_name, dir=path) 
6287   
6288                      # Loop over the lines. 
6289                      for i, data_i in enumerate(data): 
6290                          print(i, data_i) 
6291   
6292   
6293          # Do minimisation individual. 
6294          if True: 
6295              methods = ['FT', 'MDD'] 
6296              # Now calculate R2eff. 
6297              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6298   
6299              min_methods = [['FT'], ['MDD']] 
6300              min_list_glob_ini = [[128], range(126, 130, 2)[::-1]] 
6301   
6302              #min_methods = [['FT']] 
6303              #min_list_glob_ini = [[128]] 
6304              #selection = ':2,3' 
6305              selection = None 
6306   
6307              for i, methods in enumerate(min_methods): 
6308                  list_glob_ini = min_list_glob_ini[i] 
6309   
6310                  if True: 
6311                      # First get data. 
6312                      if True: 
6313                          # First load all data. 
6314                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6315   
6316                      # Then set R20 
6317                      if True: 
6318                          # Set R20 from min R2eff in preparation for Grid search. 
6319                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6320   
6321                      # Check and print parameters. 
6322                      if True: 
6323                          # Print for pipe name 
6324                          method = methods[0] 
6325                          glob_ini = list_glob_ini[0] 
6326   
6327                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6328                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6329   
6330                      # Then Grid search. 
6331                      if True: 
6332                          # Do Grid search. 
6333                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6334   
6335                  # Then Minimise. 
6336                  if True: 
6337                      # Minimise 
6338                      RDR.opt_max_iterations = int(1e2) 
6339                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6340   
6341                  #print asd 
6342   
6343          # Plot statistics. 
6344          # Try plot some minimisation correlations. 
6345          if True: 
6346              selections = [None, ':2,3'] 
6347              for selection in selections: 
6348                  # Collect param values. 
6349                  analysis = 'min_ind' 
6350                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6351                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=range(126, 130, 2)[::-1], selection=selection) 
6352   
6353                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6354                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6355                  corr_data = [fig1, fig2] 
6356   
6357                  write_stats = True 
6358                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6359   
6360                  # Open stat file. 
6361                  if write_stats: 
6362                      for i, corr_data_i in enumerate(corr_data): 
6363                          data, methods, glob_inis = corr_data[i] 
6364                          data_x, data_y = data 
6365                          method_x, method_y = methods 
6366                          glob_ini_x, glob_ini_y = glob_inis 
6367   
6368                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6369   
6370                          if selection == None: 
6371                              file_name = file_name_ini + '_all.txt' 
6372                          else: 
6373                              file_name = file_name_ini + '_sel.txt' 
6374                          path = RDR.results_dir 
6375                          data = extract_data(file=file_name, dir=path) 
6376   
6377                          # Loop over the lines. 
6378                          for i, data_i in enumerate(data): 
6379                              print(i, data_i) 
6380   
6381          # Try plot some minimisation statistics. 
6382          if True: 
6383              # Collect param values. 
6384              #selections = [None, ':2,3'] 
6385              selections = [None, ':2,3'] 
6386              for selection in selections: 
6387                  analysis = 'min_ind' 
6388                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6389                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=range(126, 130, 2)[::-1], selection=selection) 
6390   
6391                  # Get param stats. 
6392                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6393   
6394                  ## Plot R2eff stats 
6395                  write_stats = True 
6396                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6397   
6398                  # Open stat file. 
6399                  if write_stats: 
6400                      if selection == None: 
6401                          file_name = '%s_stat_all.txt' % (analysis) 
6402                      else: 
6403                          file_name = '%s_stat_sel.txt' % (analysis) 
6404                      path = RDR.results_dir 
6405                      data = extract_data(file=file_name, dir=path) 
6406   
6407                      # Loop over the lines. 
6408                      for i, data_i in enumerate(data): 
6409                          print(i, data_i) 
6410   
6411   
6412          # Do minimisation clustered. 
6413          if True: 
6414              methods = ['FT', 'MDD'] 
6415              # Now calculate R2eff. 
6416              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6417   
6418              min_methods = [['FT'], ['MDD']] 
6419              min_list_glob_ini = [[128], range(126, 130, 2)[::-1]] 
6420   
6421              #min_methods = [['FT']] 
6422              #min_list_glob_ini = [[128]] 
6423              selection = ':2,3' 
6424   
6425              for i, methods in enumerate(min_methods): 
6426                  list_glob_ini = min_list_glob_ini[i] 
6427   
6428                  if True: 
6429                      # First get data. 
6430                      if True: 
6431                          # First load all data. 
6432                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6433                       
6434                      # Then select spins. 
6435                      if True: 
6436                          # Deselect all spins. 
6437                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6438                   
6439                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6440                   
6441                      # Then preset values. 
6442                      if True: 
6443                          # Set k_AB for Grid search. 
6444                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6445                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6446                   
6447                      # Then set R20 
6448                      if True: 
6449                          # Set R20 from min R2eff in preparation for Grid search. 
6450                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6451                   
6452                      # Check and print parameters. 
6453                      if True: 
6454                          # Print for pipe name 
6455                          method = methods[0] 
6456                          glob_ini = list_glob_ini[0] 
6457   
6458                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6459                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6460                       
6461                      # Then Grid search. 
6462                      if True: 
6463                          # Do Grid search. 
6464                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6465                   
6466                      # Then cluster spins. 
6467                      if True: 
6468                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6469               
6470                  # Then Minimise. 
6471                  if True: 
6472                      # Minimise 
6473                      RDR.opt_max_iterations = int(1e2) 
6474                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6475   
6476          # Plot statistics. 
6477          # Try plot some minimisation correlations. 
6478          if True: 
6479              selection = ':2,3' 
6480              # Collect param values. 
6481              analysis = 'min' 
6482              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6483              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=range(126, 130, 2)[::-1], selection=selection) 
6484   
6485              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6486              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6487              corr_data = [fig1, fig2] 
6488   
6489              write_stats = True 
6490              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6491   
6492              # Open stat file. 
6493              if write_stats: 
6494                  for i, corr_data_i in enumerate(corr_data): 
6495                      data, methods, glob_inis = corr_data[i] 
6496                      data_x, data_y = data 
6497                      method_x, method_y = methods 
6498                      glob_ini_x, glob_ini_y = glob_inis 
6499   
6500                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6501   
6502                      if selection == None: 
6503                          file_name = file_name_ini + '_all.txt' 
6504                      else: 
6505                          file_name = file_name_ini + '_sel.txt' 
6506                      path = RDR.results_dir 
6507                      data = extract_data(file=file_name, dir=path) 
6508   
6509                      # Loop over the lines. 
6510                      for i, data_i in enumerate(data): 
6511                          print(i, data_i) 
6512   
6513          # Try plot some minimisation statistics. 
6514          if True: 
6515              # Collect param values. 
6516              selections = [':2,3'] 
6517              for selection in selections: 
6518                  analysis = 'min' 
6519                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6520                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=range(126, 130, 2)[::-1], selection=selection) 
6521   
6522                  # Get param stats. 
6523                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6524   
6525                  ## Plot R2eff stats 
6526                  write_stats = True 
6527                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6528   
6529                  # Open stat file. 
6530                  if write_stats: 
6531                      if selection == None: 
6532                          file_name = '%s_stat_all.txt' % (analysis) 
6533                      else: 
6534                          file_name = '%s_stat_sel.txt' % (analysis) 
6535                      path = RDR.results_dir 
6536                      data = extract_data(file=file_name, dir=path) 
6537   
6538                      # Loop over the lines. 
6539                      for i, data_i in enumerate(data): 
6540                          print(i, data_i) 
6541   
6542   
6543   
6544 -    def test_r1rho_kjaergaard_auto(self): 
6545          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6546   
6547          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6548   
6549          This uses the automatic analysis. 
6550   
6551          """ 
6552   
6553          # Cluster residues 
6554          cluster_ids = [ 
6555          ":13@N", 
6556          ":15@N", 
6557          ":16@N", 
6558          ":25@N", 
6559          ":26@N", 
6560          ":28@N", 
6561          ":39@N", 
6562          ":40@N", 
6563          ":41@N", 
6564          ":43@N", 
6565          ":44@N", 
6566          ":45@N", 
6567          ":49@N", 
6568          ":52@N", 
6569          ":53@N"] 
6570   
6571          # Load the data. 
6572          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6573   
6574          # Test some of the sequence. 
6575          self.assertEqual(len(cdp.mol), 1) 
6576          self.assertEqual(cdp.mol[0].name, None) 
6577          self.assertEqual(len(cdp.mol[0].res), 48) 
6578   
6579          # Test the chemical shift data. 
6580          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
6581          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
6582          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
6583          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
6584   
6585          i = 0 
6586          for spin, spin_id in spin_loop(return_id=True): 
6587              # Check the chemical shift. 
6588              self.assertEqual(spin.chemical_shift, cs[i]) 
6589   
6590              # Increment the index. 
6591              i += 1 
6592   
6593          # Initialize counter 
6594          i = 0 
6595          j = 0 
6596          # Count instances of select/deselect 
6597          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6598              if curspin.select == True: 
6599                  i += 1 
6600              if curspin.select == False: 
6601                  j += 1 
6602   
6603          # Test number of selected/deselected spins. 
6604          self.assertEqual(i, len(cluster_ids)) 
6605          self.assertEqual(j, 48-len(cluster_ids)) 
6606   
6607          # Check the initial setup. 
6608          self.assertEqual(cdp.mol[0].res[7].num, 13) 
6609          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
6610          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
6611   
6612          self.assertEqual(cdp.mol[0].res[9].num, 15) 
6613          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
6614          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
6615   
6616          self.assertEqual(cdp.mol[0].res[10].num, 16) 
6617          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
6618          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
6619   
6620          self.assertEqual(cdp.mol[0].res[16].num, 25) 
6621          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
6622          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
6623   
6624          self.assertEqual(cdp.mol[0].res[17].num, 26) 
6625          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
6626          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
6627   
6628          self.assertEqual(cdp.mol[0].res[19].num, 28) 
6629          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
6630          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
6631   
6632          self.assertEqual(cdp.mol[0].res[29].num, 39) 
6633          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
6634          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
6635   
6636          self.assertEqual(cdp.mol[0].res[30].num, 40) 
6637          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
6638          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
6639   
6640          self.assertEqual(cdp.mol[0].res[31].num, 41) 
6641          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
6642          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
6643   
6644          self.assertEqual(cdp.mol[0].res[33].num, 43) 
6645          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
6646          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
6647   
6648          self.assertEqual(cdp.mol[0].res[34].num, 44) 
6649          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
6650          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
6651   
6652          self.assertEqual(cdp.mol[0].res[35].num, 45) 
6653          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
6654          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
6655   
6656          self.assertEqual(cdp.mol[0].res[38].num, 49) 
6657          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
6658          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
6659   
6660          self.assertEqual(cdp.mol[0].res[41].num, 52) 
6661          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
6662          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
6663   
6664          self.assertEqual(cdp.mol[0].res[42].num, 53) 
6665          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
6666          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
6667   
6668          # The dispersion models. 
6669          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6670   
6671          # The grid search size (the number of increments per dimension). 
6672          GRID_INC = 4 
6673   
6674          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6675          MC_NUM = 3 
6676   
6677          # Model selection technique. 
6678          MODSEL = 'AIC' 
6679   
6680          # Execute the auto-analysis (fast). 
6681          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6682          OPT_FUNC_TOL = 1e-1 
6683          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6684          OPT_MAX_ITERATIONS = 1000 
6685          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6686   
6687          result_dir_name = ds.tmpdir 
6688   
6689          # Make all spins free 
6690          for curspin in cluster_ids: 
6691              self.interpreter.relax_disp.cluster('free spins', curspin) 
6692              # Shut them down 
6693              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6694   
6695          # Select only a subset of spins for global fitting 
6696          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6697          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6698   
6699          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6700          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6701   
6702          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6703          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6704   
6705          # Run the analysis. 
6706          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6707   
6708          # Check the kex value of residue 52 
6709          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
6710   
6711          # Print results for each model. 
6712          print("\n\n################") 
6713          print("Printing results") 
6714          print("################\n") 
6715          for model in MODELS: 
6716              # Skip R2eff model. 
6717              if model == MODEL_R2EFF: 
6718                  continue 
6719   
6720              # Switch to pipe. 
6721              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
6722              print("\nModel: %s" % (model)) 
6723   
6724              # Loop over the spins. 
6725              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6726                  # Generate spin string. 
6727                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
6728   
6729                  # Loop over the parameters. 
6730                  print("Optimised parameters for spin: %s" % (spin_string)) 
6731                  for param in cur_spin.params + ['chi2']: 
6732                      # Get the value. 
6733                      if param in ['r1', 'r2']: 
6734                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
6735                              # Generate the R20 key. 
6736                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
6737   
6738                              # Get the value. 
6739                              value = getattr(cur_spin, param)[r20_key] 
6740   
6741                              # Print value. 
6742                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6743   
6744                      # For all other parameters. 
6745                      else: 
6746                          # Get the value. 
6747                          value = getattr(cur_spin, param) 
6748   
6749                          # Print value. 
6750                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6751   
6752          # Print the final pipe. 
6753          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
6754          print("\nFinal pipe") 
6755   
6756   
6757 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
6758          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
6759   
6760          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6761   
6762          This uses the automatic analysis. 
6763   
6764          """ 
6765   
6766          # Cluster residues 
6767          cluster_ids = [ 
6768          ":52@N"] 
6769   
6770          # Load the data. 
6771          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6772   
6773          # The dispersion models. 
6774          MODELS = [MODEL_R2EFF] 
6775   
6776          # The grid search size (the number of increments per dimension). 
6777          GRID_INC = 4 
6778   
6779          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6780          MC_NUM = 3 
6781   
6782          # Model selection technique. 
6783          MODSEL = 'AIC' 
6784   
6785          # Execute the auto-analysis (fast). 
6786          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6787          OPT_FUNC_TOL = 1e-1 
6788          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6789          OPT_MAX_ITERATIONS = 1000 
6790          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6791   
6792          result_dir_name = ds.tmpdir 
6793   
6794          # Make all spins free 
6795          for curspin in cluster_ids: 
6796              self.interpreter.relax_disp.cluster('free spins', curspin) 
6797              # Shut them down 
6798              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6799   
6800          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6801   
6802          # Run the analysis. 
6803          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6804   
6805          # Check the graphs produced. 
6806          graph_comb = [ 
6807          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
6808          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
6809          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
6810          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
6811          ] 
6812   
6813          # Define expected folder names. 
6814          result_folders = MODELS 
6815   
6816          # Assign spin_id. 
6817          spin_id = ':52@N' 
6818   
6819          # Loop over result folders. 
6820          for result_folder in result_folders: 
6821              # Skip the model R2eff, which does not produce graphs. 
6822              if result_folder == MODEL_R2EFF: 
6823                  continue 
6824   
6825              # Loop over graphs. 
6826              for y_axis, x_axis, interpolate in graph_comb: 
6827                  # Determine file name: 
6828                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
6829   
6830                  # Make the file name. 
6831                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
6832   
6833                  # Get the file path. 
6834                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
6835   
6836                  print("Testing file access to graph: %s"%file_path) 
6837                  self.assert_(access(file_path, F_OK)) 
6838   
6839          # Start testing all possible combinations of graphs. 
6840          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
6841          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
6842          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
6843   
6844          result_dir_name = ds.tmpdir 
6845   
6846          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
6847          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
6848   
6849          for result_folder in result_folders: 
6850              # Skip the model R2eff, which does not produce graphs. 
6851              if result_folder == MODEL_R2EFF: 
6852                  continue 
6853   
6854              for y_axis in y_axis_types: 
6855                  for x_axis in x_axis_types: 
6856                      for interpolate in interpolate_types: 
6857                          # Determine file name: 
6858                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
6859   
6860                          # Make the file name. 
6861                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
6862   
6863                          # Write the curves. 
6864                          dir = result_dir_name+sep+result_folder 
6865                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
6866                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
6867   
6868                          # Get the file path. 
6869                          file_path = get_file_path(file_name, dir) 
6870   
6871                          # Test the plot file exists. 
6872                          print("Testing file access to graph: %s"%file_path) 
6873                          self.assert_(access(file_path, F_OK)) 
6874   
6875                          # Now open, and compare content, line by line. 
6876                          file_prod = open(file_path) 
6877                          lines_prod = file_prod.readlines() 
6878                          file_prod.close() 
6879   
6880                          # Define file to compare against. 
6881                          dir_comp = data_path+sep+result_folder 
6882                          file_path_comp = get_file_path(file_name, dir_comp) 
6883                          file_comp = open(file_path_comp) 
6884                          lines_comp = file_comp.readlines() 
6885                          file_comp.close() 
6886   
6887                          # Assert number of lines is equal. 
6888                          self.assertEqual(len(lines_prod), len(lines_comp)) 
6889                          for j in range(len(lines_prod)): 
6890                              # Make the string test 
6891                              first_char = lines_prod[j][0] 
6892                              if first_char in ["@", "&"]: 
6893                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
6894                              else: 
6895                                  # Split string in x, y, error. 
6896                                  # The error would change per run. 
6897                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
6898                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
6899                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
6900                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
6901   
6902   
6903 -    def test_r1rho_kjaergaard_missing_r1(self): 
6904          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6905   
6906          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6907   
6908          This uses the automatic analysis, with missing loading R1. 
6909   
6910          """ 
6911   
6912          # Cluster residues 
6913          cluster_ids = [ 
6914          ":13@N", 
6915          ":15@N", 
6916          ":16@N", 
6917          ":25@N", 
6918          ":26@N", 
6919          ":28@N", 
6920          ":39@N", 
6921          ":40@N", 
6922          ":41@N", 
6923          ":43@N", 
6924          ":44@N", 
6925          ":45@N", 
6926          ":49@N", 
6927          ":52@N", 
6928          ":53@N"] 
6929   
6930          # Load the data. 
6931          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
6932   
6933          # The dispersion models. 
6934          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6935   
6936          # The grid search size (the number of increments per dimension). 
6937          GRID_INC = None 
6938   
6939          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6940          MC_NUM = 3 
6941   
6942          # Model selection technique. 
6943          MODSEL = 'AIC' 
6944   
6945          # Execute the auto-analysis (fast). 
6946          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6947          OPT_FUNC_TOL = 1e-25 
6948          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6949          OPT_MAX_ITERATIONS = 10000000 
6950          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6951   
6952          result_dir_name = ds.tmpdir 
6953   
6954          # Make all spins free 
6955          for curspin in cluster_ids: 
6956              self.interpreter.relax_disp.cluster('free spins', curspin) 
6957              # Shut them down 
6958              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6959   
6960          # Select only a subset of spins for global fitting 
6961          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6962          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6963   
6964          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6965          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6966   
6967          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6968          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6969   
6970          # Point to directory with R2eff values, with 2000 MC simulations. 
6971          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
6972   
6973          r1_fit = True 
6974   
6975          # Run the analysis. 
6976          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
6977   
6978          # Verify the data. 
6979          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
6980   
6981   
6982 -    def test_r2eff_read(self): 
6983          """Test the operation of the relax_disp.r2eff_read user function.""" 
6984   
6985          # The path to the data files. 
6986          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
6987   
6988          # Read the sequence data. 
6989          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
6990   
6991          # The ID. 
6992          id = 'test' 
6993   
6994          # Set up the metadata. 
6995          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
6996          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
6997   
6998          # Try reading the file. 
6999          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7000   
7001          # Check the global data. 
7002          data = [ 
7003              ['cpmg_frqs', {'test': 66.667}], 
7004              ['cpmg_frqs_list', [66.667]], 
7005              ['dispersion_points', 1], 
7006              ['exp_type', {'test': 'SQ CPMG'}], 
7007              ['exp_type_list', ['SQ CPMG']], 
7008              ['spectrometer_frq', {'test': 800000000.0}], 
7009              ['spectrometer_frq_count', 1], 
7010              ['spectrometer_frq_list', [800000000.0]], 
7011              ['spectrum_ids', ['test']] 
7012          ] 
7013          for name, value in data: 
7014              # Does it exist? 
7015              self.assert_(hasattr(cdp, name)) 
7016   
7017              # Check the object. 
7018              obj = getattr(cdp, name) 
7019              self.assertEqual(obj, value) 
7020   
7021          # Check the spin data. 
7022          data = [ 
7023              [1,       2.3035747e+04, 8.5467725e+01], 
7024              [2,       9.9629762e+04, 2.8322033e+02], 
7025              [3,       9.5663137e+04, 2.8632929e+02], 
7026              [4,       1.7089893e+05, 3.1089428e+02], 
7027              [5,       4.7323876e+04, 1.0084269e+02], 
7028              [6,       2.0199122e+04, 1.0135220e+02], 
7029              [7,       1.6655488e+05, 3.1609061e+02], 
7030              [8,       9.0061074e+04, 1.9176585e+02], 
7031              [10,      8.4726204e+04, 2.8898155e+02], 
7032              [11,      1.5050233e+05, 4.3138029e+02], 
7033              [12,      9.2998531e+04, 3.0440191e+02], 
7034              [13,      1.6343507e+05, 3.3144097e+02], 
7035              [14,      1.0137301e+05, 3.7314642e+02], 
7036              [15,      8.3407837e+04, 1.6546473e+02], 
7037              [16,      1.3819126e+05, 3.3388517e+02], 
7038              [17,      1.1010490e+05, 3.5639222e+02], 
7039              [18,      9.4324035e+04, 3.2343585e+02], 
7040              [19,      1.1135179e+05, 3.0706671e+02], 
7041              [20,      7.6339410e+04, 1.7377460e+02], 
7042              [21,      6.2008453e+04, 1.7327150e+02], 
7043              [22,      1.0590404e+05, 2.4814635e+02], 
7044              [23,      1.0630198e+05, 2.3601100e+02], 
7045              [24,      7.2996320e+04, 1.4952465e+02], 
7046              [25,      9.5486742e+04, 2.7080766e+02], 
7047              [26,      5.8067989e+04, 1.6820462e+02], 
7048              [27,     -1.7168510e+04, 2.2519560e+02], 
7049              [28,      1.6891473e+05, 2.3497525e+02], 
7050              [29,      9.4038555e+04, 2.0357593e+02], 
7051              [30,      2.1386951e+04, 2.2153532e+02], 
7052              [31,      9.3982899e+04, 2.0937056e+02], 
7053              [32,      8.6097484e+04, 2.3868467e+02], 
7054              [33,      1.0194337e+05, 2.7370704e+02], 
7055              [34,      8.5683111e+04, 2.0838076e+02], 
7056              [35,      8.6985768e+04, 2.0889310e+02], 
7057              [36,      8.6011237e+04, 1.7498390e+02], 
7058              [37,      1.0984097e+05, 2.7622998e+02], 
7059              [38,      8.7017879e+04, 2.6547994e+02], 
7060              [39,      9.1682649e+04, 5.2777676e+02], 
7061              [40,      7.6370440e+04, 1.9873214e+02], 
7062              [41,      9.1393531e+04, 2.4483824e+02], 
7063              [42,      1.1017111e+05, 2.8020699e+02], 
7064              [43,      9.4552366e+04, 3.4394150e+02], 
7065              [44,      1.2858281e+05, 6.8449252e+02], 
7066              [45,      7.4583525e+04, 1.9544210e+02], 
7067              [46,      9.2087490e+04, 2.0491066e+02], 
7068              [47,      9.7507255e+04, 2.5162839e+02], 
7069              [48,      1.0033842e+05, 2.7566430e+02], 
7070              [49,      1.3048305e+05, 2.6797466e+02], 
7071              [50,      1.0546796e+05, 1.9304384e+02], 
7072              [51,      9.3099697e+04, 2.0773311e+02], 
7073              [52,      4.6863758e+04, 1.3169068e+02], 
7074              [53,      6.1055806e+04, 1.5448477e+02], 
7075              [55,      6.8629994e+04, 1.6868673e+02], 
7076              [56,      1.1005552e+05, 2.1940465e+02], 
7077              [57,      1.0572760e+05, 1.9768486e+02], 
7078              [58,      1.1176950e+05, 3.0009610e+02], 
7079              [59,      9.8758603e+04, 3.3803895e+02], 
7080              [60,      9.9517201e+04, 3.5137994e+02], 
7081              [61,      5.4357946e+04, 2.5896579e+02], 
7082              [62,      1.0899978e+05, 2.8720371e+02], 
7083              [63,      8.4549759e+04, 4.1401837e+02], 
7084              [64,      5.5014550e+04, 2.1135781e+02], 
7085              [65,      8.0569666e+04, 2.3249709e+02], 
7086              [66,      1.2936610e+05, 3.5218725e+02], 
7087              [67,      3.6438010e+04, 8.7924003e+01], 
7088              [70,      3.8763157e+04, 1.3325040e+02], 
7089              [71,      8.5711411e+04, 2.9316183e+02], 
7090              [72,      3.3211541e+04, 1.2182123e+02], 
7091              [73,      3.2070576e+04, 1.2305430e+02] 
7092          ] 
7093          for res_num, value, error in data: 
7094              # Get the spin. 
7095              spin = return_spin(spin_id=":%s"%res_num) 
7096   
7097              # Check the values. 
7098              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7099              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7100   
7101   
7102 -    def test_r2eff_read_spin(self): 
7103          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7104   
7105          # The path to the data files. 
7106          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7107   
7108          # Generate the sequence. 
7109          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7110          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7111          self.interpreter.spin.isotope('1H', spin_id='@H') 
7112          self.interpreter.spin.isotope('15N', spin_id='@N') 
7113   
7114          # Build the experiment IDs. 
7115          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7116          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7117          ids = [] 
7118          for value in H_disp_points: 
7119              ids.append('1H_CPMG_%s' % value) 
7120          for value in N_disp_points: 
7121              ids.append('15N_CPMG_%s' % value) 
7122          print("\n\nThe experiment IDs are %s." % ids) 
7123   
7124          # Set up the metadata for the experiments. 
7125          for id in ids: 
7126              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7127              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7128          for value in H_disp_points: 
7129              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7130          for value in N_disp_points: 
7131              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7132   
7133          # Loop over the experiments. 
7134          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7135              # Try reading the file. 
7136              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7137   
7138          # Check the global data. 
7139          data = [ 
7140              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7141              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7142              ['dispersion_points', 24], 
7143              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7144              ['exp_type_list', ['SQ CPMG']], 
7145              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7146              ['spectrometer_frq_count', 1], 
7147              ['spectrometer_frq_list', [500000000.0]], 
7148              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7149          ] 
7150          for name, value in data: 
7151              # Does it exist? 
7152              self.assert_(hasattr(cdp, name)) 
7153   
7154              # Check the object. 
7155              obj = getattr(cdp, name) 
7156              if not isinstance(data, dict): 
7157                  self.assertEqual(obj, value) 
7158   
7159              # Check the global dictionary data. 
7160              else: 
7161                  for id in ids: 
7162                      self.assertEqual(obj[id], value[id]) 
7163   
7164          # Check the spin data. 
7165          h_data = [ 
7166              [  67.0,  21.47924,   0.42958], 
7167              [ 133.0,  16.73898,   0.33478], 
7168              [ 267.0,   9.97357,   0.19947], 
7169              [ 400.0,   8.23877,   0.24737], 
7170              [ 533.0,   7.59290,   0.24263], 
7171              [ 667.0,   7.45843,   0.24165], 
7172              [ 800.0,   7.11222,   0.23915], 
7173              [ 933.0,   7.40880,   0.24129], 
7174              [1067.0,   6.55191,   0.16629], 
7175              [1600.0,   6.72177,   0.23637], 
7176              [2133.0,   7.09629,   0.23904], 
7177              [2667.0,   7.14675,   0.23940] 
7178          ] 
7179          for disp_point, value, error in h_data: 
7180              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7181              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7182              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7183          n_data = [ 
7184              [  50.0,  27.15767,   0.54315], 
7185              [ 100.0,  26.55781,   0.53116], 
7186              [ 150.0,  24.73462,   0.49469], 
7187              [ 200.0,  20.98617,   0.41972], 
7188              [ 250.0,  17.82442,   0.35649], 
7189              [ 300.0,  15.55352,   0.31107], 
7190              [ 350.0,  13.78958,   0.27579], 
7191              [ 400.0,  12.48334,   0.24967], 
7192              [ 500.0,  11.55724,   0.23114], 
7193              [ 600.0,  10.53874,   0.21077], 
7194              [ 700.0,  10.07395,   0.20148], 
7195              [ 800.0,   9.62952,   0.19259], 
7196              [ 900.0,   9.49994,   0.19000], 
7197              [1000.0,   8.71350,   0.17427] 
7198          ] 
7199          for disp_point, value, error in n_data: 
7200              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7201              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7202              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7203   
7204   
7205 -    def test_r2eff_fit_fixed_time(self): 
7206          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7207   
7208          # Execute the script. 
7209          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7210   
7211   
7212 -    def test_read_r2eff(self): 
7213          """Test the reading of a file containing r2eff values.""" 
7214   
7215          # Create the sequence data, and name the spins. 
7216          self.interpreter.residue.create(1, 'Gly') 
7217          self.interpreter.residue.create(2, 'Gly') 
7218          self.interpreter.residue.create(3, 'Gly') 
7219   
7220          # Read the file. 
7221          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7222   
7223          # Test the data. 
7224          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7225          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7226          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7227   
7228   
7229 -    def test_r20_from_min_r2eff_cpmg(self): 
7230          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7231   
7232          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7233   
7234          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7235          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7236   
7237          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7238          Data is for experiment at 25 degree Celcius. 
7239          """ 
7240   
7241          # Base data setup. 
7242          pipe_name = 'base pipe' 
7243          pipe_type = 'relax_disp' 
7244          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7245          select_spin_index = list(range(0, 1)) 
7246          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7247   
7248          # Generate r20 key. 
7249          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7250          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7251   
7252          ## Now prepare for MODEL calculation. 
7253          MODEL = "CR72" 
7254   
7255          # Change pipe. 
7256          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7257          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7258          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7259   
7260          # Then select model. 
7261          self.interpreter.relax_disp.select_model(model=MODEL) 
7262   
7263          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7264          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7265   
7266          # Test result, for normal run. 
7267          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7268              # Get the spin_params. 
7269              spin_params = spin.params 
7270   
7271              # Defined fixed values for testing. 
7272              if spin_id == ":10@N": 
7273                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7274                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7275   
7276              # Print out. 
7277              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7278   
7279              # Testing the r2 values for the different fields are not the same. 
7280              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7281   
7282              # Test values are larger than 0. 
7283              self.assert_(spin.r2[r20_key_600] > 0.0) 
7284              self.assert_(spin.r2[r20_key_500] > 0.0) 
7285   
7286              # Loop over the experiment settings. 
7287              r2eff_600 = [] 
7288              r2eff_500 = [] 
7289              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7290                  # Create the data key. 
7291                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7292   
7293                  # Extract the r2 eff data. 
7294                  r2eff = spin.r2eff[data_key] 
7295                  if frq == 599.8908617*1E6: 
7296                      r2eff_600.append(r2eff) 
7297                  elif frq == 499.862139*1E6: 
7298                      r2eff_500.append(r2eff) 
7299   
7300              # Sort values. 
7301              r2eff_600.sort() 
7302              r2eff_500.sort() 
7303   
7304              # Test values again. 
7305              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7306              print(r2eff_600) 
7307              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7308              print("") 
7309   
7310              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7311              print(r2eff_500) 
7312              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7313              print("") 
7314   
7315          print("###########################################") 
7316          print("Trying GRID SEARCH for minimum R2eff values") 
7317   
7318          ### Test just the Grid search. 
7319          GRID_INC = 5 
7320   
7321          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7322   
7323          ### Then test the value.set function. 
7324          # Change pipe. 
7325          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7326          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7327          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7328   
7329          # Then select model. 
7330          self.interpreter.relax_disp.select_model(model=MODEL) 
7331   
7332          # Then set the standard parameter values. 
7333          for param in spin_params: 
7334              print("Setting standard parameter for param: %s"%param) 
7335              self.interpreter.value.set(param=param, index=None) 
7336   
7337          # Test result, for normal run. 
7338          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7339              # Print out. 
7340              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7341   
7342              # Testing the r2 values. 
7343              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7344              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7345              self.assertEqual(spin.pA, 0.9) 
7346              self.assertEqual(spin.dw, 1.0) 
7347              self.assertEqual(spin.kex, 1000.0) 
7348   
7349          print("###########################################") 
7350          print("Trying GRID SEARCH for standard R2eff values") 
7351   
7352          ### Test just the Grid search. 
7353          GRID_INC = 5 
7354   
7355          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7356   
7357          ### Run auto_analysis. 
7358          # The grid search size (the number of increments per dimension). 
7359          GRID_INC = 5 
7360   
7361          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7362          MC_NUM = 3 
7363   
7364          # Model selection technique. 
7365          MODSEL = 'AIC' 
7366   
7367          # Execute the auto-analysis (fast). 
7368          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7369          OPT_FUNC_TOL = 1e-1 
7370          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7371          OPT_MAX_ITERATIONS = 1000 
7372          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7373   
7374          # Run the analysis. 
7375          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7376   
7377   
7378 -    def test_show_apod_extract(self): 
7379          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7380   
7381          # The path to the data files. 
7382          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7383   
7384          # Define file name. 
7385          file_name = '128_0_FT.ft2' 
7386   
7387          # Call function. 
7388          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7389   
7390          # Define how output should look like. 
7391          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7392          # Dont test lines which can differ. 
7393          show_apod_ver = [ 
7394              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7395              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7396              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7397              '', 
7398              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7399              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7400              #'', 
7401              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7402              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7403   
7404          for i, line in enumerate(show_apod_ver): 
7405              line_ver = get_output[i] 
7406   
7407              print(line) 
7408              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7409                  continue 
7410              # Make the string test 
7411              self.assertEqual(line, line_ver) 
7412   
7413   
7414 -    def test_show_apod_rmsd(self): 
7415          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7416   
7417          # The path to the data files. 
7418          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7419   
7420          # Define file name. 
7421          file_name = '128_0_FT.ft2' 
7422   
7423          # Call function. 
7424          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7425   
7426          # Assert. 
7427          self.assertEqual(rmsd, 8583.41) 
7428   
7429   
7430 -    def test_show_apod_rmsd_dir_to_files(self): 
7431          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7432   
7433          # The path to the data files. 
7434          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7435   
7436          # Call function, and get all file names. 
7437          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7438   
7439          # Loop over file_paths. 
7440          for wfile_path in wfile_paths: 
7441              # Open the file. 
7442              get_data = extract_data(file=wfile_path) 
7443   
7444              # Extract line 0, column 0. 
7445              test = float(get_data[0][0]) 
7446   
7447              # Assert. 
7448              self.assertEqual(test, 8583.41) 
7449   
7450   
7451 -    def test_show_apod_rmsd_to_file(self): 
7452          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7453   
7454          # The path to the data files. 
7455          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7456   
7457          # Define file name. 
7458          file_name = '128_0_FT.ft2' 
7459   
7460          # Call function, and get file name. 
7461          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7462   
7463          # Open the file. 
7464          get_data = extract_data(file=wfile_path) 
7465   
7466          # Extract line 0, column 0. 
7467          test = float(get_data[0][0]) 
7468   
7469          # Assert. 
7470          self.assertEqual(test, 8583.41) 
7471   
7472   
7473 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7474          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7475   
7476          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7477          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7478   
7479          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7480          Data is for experiment at 25 degree Celcius. 
7481   
7482          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7483          """ 
7484   
7485          # Base data setup. 
7486          pipe_name = 'base pipe' 
7487          pipe_type = 'relax_disp' 
7488          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7489          select_spin_index = list(range(0, 1)) 
7490          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7491   
7492          # Define replicated 
7493          repl_A = ['Z_A1', 'Z_A15'] 
7494          repl_B = ['Z_B1', 'Z_B18'] 
7495   
7496          # Loop over spectrum ID, and sort them 
7497          spectrum_ids_A = [] 
7498          spectrum_ids_B = [] 
7499          for spectrum_id in cdp.spectrum_ids: 
7500              if "A" in spectrum_id: 
7501                  spectrum_ids_A.append(spectrum_id) 
7502              elif "B" in spectrum_id: 
7503                  spectrum_ids_B.append(spectrum_id) 
7504   
7505          # To clean up old error analysis, delete attributes 
7506          delattr(cdp, "var_I") 
7507          delattr(cdp, "sigma_I") 
7508   
7509          # Perform error analysis 
7510          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7511          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7512   
7513          # Loop over spins, save errors to list 
7514          Errors_A_B = [] 
7515          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7516              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7517              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7518              Errors_A_B.append([A_err, B_err]) 
7519   
7520          # To clean up old error analysis, delete attributes 
7521          delattr(cdp, "var_I") 
7522          delattr(cdp, "sigma_I") 
7523   
7524          # Perform error analysis. Order is important 
7525          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7526          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7527   
7528          # Loop over spins, save errors to list 
7529          Errors_B_A = [] 
7530          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7531              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7532              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7533              Errors_B_A.append([A_err, B_err]) 
7534   
7535          # Make test for order of error 
7536          for i in range(len(Errors_A_B)): 
7537              Error_A_B = Errors_A_B[i] 
7538              Error_B_A = Errors_B_A[i] 
7539              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7540              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7541   
7542          # Make further tests for fixed values 
7543          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7544          std_A_fix = 2785.7263335738567 
7545   
7546          for id_A in spectrum_ids_A: 
7547              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7548              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7549   
7550          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7551          std_B_fix = 4967.3772030667988 
7552   
7553          for id_B in spectrum_ids_B: 
7554              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7555              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7556   
7557   
7558 -    def test_sod1wt_t25_to_cr72(self): 
7559          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7560   
7561          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7562          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7563   
7564          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7565          Data is for experiment at 25 degree Celcius. 
7566          """ 
7567   
7568          # Base data setup. 
7569          pipe_name = 'base pipe' 
7570          pipe_type = 'relax_disp' 
7571          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7572          select_spin_index = list(range(0, 2)) 
7573          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7574   
7575          # Generate r20 key. 
7576          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7577          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7578   
7579          ## Now prepare for MODEL calculation. 
7580          MODEL = "CR72" 
7581   
7582          # Change pipe. 
7583          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7584          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7585          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7586   
7587          # Then select model. 
7588          self.interpreter.relax_disp.select_model(model=MODEL) 
7589   
7590          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
7591          GRID_INC = 7 
7592   
7593          # Store grid and minimisations results. 
7594          grid_results = [] 
7595          mini_results = [] 
7596          clust_results = [] 
7597   
7598          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7599          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7600   
7601          # Deselect insignificant spins. 
7602          self.interpreter.relax_disp.insignificance(level=1.0) 
7603   
7604          # Perform Grid Search. 
7605          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7606   
7607          # Store result. 
7608          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7609              # Store grid results. 
7610              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7611   
7612          ## Now do minimisation. 
7613          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7614          set_func_tol = 1e-9 
7615          set_max_iter = 100000 
7616          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7617   
7618          # Store result. 
7619          pA_values = [] 
7620          kex_values = [] 
7621          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7622              # Store minimisation results. 
7623              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7624   
7625              # Store pA values. 
7626              pA_values.append(spin.pA) 
7627   
7628              # Store kex values. 
7629              kex_values.append(spin.kex) 
7630   
7631          print("\n# Now print before and after minimisation.\n") 
7632   
7633          # Print results. 
7634          for i in range(len(grid_results)): 
7635              # Get values. 
7636              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7637              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7638   
7639              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7640              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7641   
7642          ## Prepare for clustering 
7643          # Change pipe. 
7644          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
7645          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
7646          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
7647   
7648          # Then select model. 
7649          self.interpreter.relax_disp.select_model(model=MODEL) 
7650   
7651          # Define cluster id. 
7652          cluster_id = 'clust' 
7653   
7654          # Loop over spins to cluster them. 
7655          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7656              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
7657   
7658          # Copy over values. 
7659          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
7660   
7661          # Test the median values is correct 
7662          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7663              print(pA_values) 
7664              # The the median pA value returned. 
7665              self.assertEqual(median(pA_values), spin.pA) 
7666   
7667              # The the median kex value returned. 
7668              self.assertEqual(median(kex_values), spin.kex) 
7669   
7670          ## Now do minimisation. 
7671          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7672   
7673          # Store result. 
7674          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7675              # Store clust results. 
7676              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7677   
7678              # Store the outcome of the clustering minimisation. 
7679              clust_pA = spin.pA 
7680              clust_kex = spin.kex 
7681   
7682          print("\n# Now testing.\n") 
7683   
7684          # Define results 
7685          test_res = {} 
7686          test_res[':10@N'] = {} 
7687          test_res[':10@N']['r2600'] = 18.429755324773360 
7688          test_res[':10@N']['r2500'] = 16.981349161968630 
7689          test_res[':10@N']['dw'] = 2.700755859433969 
7690          test_res[':10@N']['pA'] = 0.971531659288657 
7691          test_res[':10@N']['kex'] = 3831.766337047963134 
7692          test_res[':11@N'] = {} 
7693          test_res[':11@N']['r2600'] = 18.193409421115213 
7694          test_res[':11@N']['r2500'] = 17.308838135567765 
7695          test_res[':11@N']['dw'] = 2.706650302761793 
7696          test_res[':11@N']['pA'] = 0.971531659288657 
7697          test_res[':11@N']['kex'] = 3831.766337047963134 
7698   
7699          # Then make tests. 
7700          for i in range(len(grid_results)): 
7701              # Get values. 
7702              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7703              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7704              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
7705   
7706              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7707              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7708              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
7709   
7710              # Make tests. 
7711              self.assertEqual(clust_pA, c_pA) 
7712              self.assertEqual(clust_kex, c_kex) 
7713   
7714              # Test values. 
7715              if c_spin_id in test_res: 
7716                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
7717                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
7718                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
7719                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
7720                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
7721   
7722          # Save disp graph to temp. 
7723          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
7724   
7725   
7726 -    def test_sod1wt_t25_to_sherekhan_input(self): 
7727          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
7728   
7729          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7730          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7731   
7732          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7733          Data is for experiment at 25 degree Celcius. 
7734          """ 
7735   
7736          # Base data setup. 
7737          pipe_name = 'base pipe' 
7738          pipe_type = 'relax_disp' 
7739          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7740          select_spin_index = list(range(0, 2)) 
7741          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7742   
7743          # Generate r20 key. 
7744          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7745          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7746   
7747          # Cluster everything, to analyse together. 
7748          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
7749   
7750          # Write input 
7751          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
7752   
7753          # Check the r2eff set files. 
7754          print("\nChecking the R2eff input set files.") 
7755          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
7756   
7757          # First check file exists 
7758          for dir, file in files: 
7759              print(dir+sep+file) 
7760              self.assert_(access(dir+sep+file, F_OK)) 
7761   
7762          # Define how files should look like 
7763          data_set_600 = [ 
7764               "60.8272464287\n", 
7765               "0.06\n", 
7766               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7767               "# G10\n", 
7768               "              33.333       26.53556078711      0.5236104771163\n", 
7769               "              66.667       25.29735243318        0.48766574122\n", 
7770               "                 100       25.09470361403      0.4820438864671\n", 
7771               "             133.333       25.15603274331      0.4837377286085\n", 
7772               "             166.667       24.27213341753      0.4599457904395\n", 
7773               "                 200       24.00364120328      0.4529773198905\n", 
7774               "             266.667       24.03511395168      0.4537880662536\n", 
7775               "                 300       23.04761040024      0.4291039120557\n", 
7776               "             333.333       22.95530300787      0.4268745963972\n", 
7777               "                 400       23.06158810662      0.4294426293624\n", 
7778               "             466.667       22.26799054092      0.4106809618644\n", 
7779               "             533.333       21.99851418823      0.4045232104735\n", 
7780               "             666.667       21.19651570955      0.3868136173831\n", 
7781               "             833.333       20.30938498379      0.3682604887899\n", 
7782               "                1000       20.28273252609       0.367719392568\n", 
7783               "# D11\n", 
7784               "              33.333       24.76520269878      0.5026475808706\n", 
7785               "              66.667        24.8773107448      0.5058752916906\n", 
7786               "                 100       24.90357815239      0.5066348551479\n", 
7787               "             133.333        23.7782506151      0.4751950583865\n", 
7788               "             166.667       23.68548762076      0.4727017128631\n", 
7789               "                 200       23.58629651618      0.4700517377679\n", 
7790               "             266.667       23.47734671187      0.4671601744044\n", 
7791               "                 300       24.08647493772      0.4835855560598\n", 
7792               "             333.333       22.98314371029      0.4542918950801\n", 
7793               "                 400       22.80339361568      0.4497107885587\n", 
7794               "             466.667       22.91634335366      0.4525833037874\n", 
7795               "             533.333       22.59774140046      0.4445334311324\n", 
7796               "             666.667        20.9177750759      0.4046955726046\n", 
7797               "             833.333       20.71792550566      0.4002363835007\n", 
7798               "                1000       19.54080006349      0.3751112751853\n", 
7799          ] 
7800   
7801          # Check data_set_600 
7802          file = open(files[0][0]+sep+files[0][1]) 
7803          lines = file.readlines() 
7804          file.close() 
7805          self.assertEqual(len(data_set_600), len(lines)) 
7806          for i in range(len(data_set_600)): 
7807              # Make the string test 
7808              self.assertEqual(data_set_600[i], lines[i]) 
7809   
7810          # Define how files should look like 
7811          data_set_500 = [ 
7812               "50.6846152368\n", 
7813               "0.04\n", 
7814               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7815               "# G10\n", 
7816               "                  50       22.28084307393      0.2944966344183\n", 
7817               "                 100       21.93494977761      0.2910362768307\n", 
7818               "                 150       21.09850032232       0.282892238351\n", 
7819               "                 200       20.86493960397      0.2806737853646\n", 
7820               "                 250       20.75287269752      0.2796178205016\n", 
7821               "                 300       20.25597152406      0.2750013546989\n", 
7822               "                 350       19.92172163467      0.2719555756504\n", 
7823               "                 400       19.97712052922       0.272457105051\n", 
7824               "                 450       19.46807010415      0.2678972122793\n", 
7825               "                 500       19.76875460947      0.2705774849203\n", 
7826               "                 550       19.39161367402      0.2672216964327\n", 
7827               "                 600       19.03949517697      0.2641417899694\n", 
7828               "                 650       19.12218812132      0.2648605059901\n", 
7829               "                 700       19.01037461457      0.2638893584683\n", 
7830               "                 800       18.83395162904      0.2623674321143\n", 
7831               "                 900       18.47529972436      0.2593123604687\n", 
7832               "                1000        18.5252023121      0.2597343394038\n", 
7833               "# D11\n", 
7834               "                  50       22.15403890237      0.3285588379827\n", 
7835               "                 100       21.80946781746      0.3247185598713\n", 
7836               "                 150       21.77715415505       0.324361526682\n", 
7837               "                 200       21.41647464235      0.3204122024881\n", 
7838               "                 250       21.17099940822      0.3177616325958\n", 
7839               "                 300       21.03740030577      0.3163316496664\n", 
7840               "                 350       20.95393648281      0.3154427665172\n", 
7841               "                 400       20.93311399332       0.315221543436\n", 
7842               "                 450       20.18219905222      0.3073848655291\n", 
7843               "                 500       19.93599065085      0.3048744697057\n", 
7844               "                 550       19.68475725452      0.3023424499113\n", 
7845               "                 600       19.33575433934      0.2988741928798\n", 
7846               "                 650       19.53915692194      0.3008886196853\n", 
7847               "                 700        19.2018754351      0.2975587767134\n", 
7848               "                 800       18.82360965368      0.2938866923878\n", 
7849               "                 900       18.71861761238      0.2928790380131\n", 
7850               "                1000       17.95878049287      0.2857341721151\n", 
7851          ] 
7852   
7853          # Check data_set_500 
7854          file = open(files[1][0]+sep+files[1][1]) 
7855          lines = file.readlines() 
7856          file.close() 
7857          self.assertEqual(len(data_set_500), len(lines)) 
7858          for i in range(len(data_set_500)): 
7859              # Make the string test 
7860              self.assertEqual(data_set_500[i], lines[i]) 
7861   
7862          # Test local dir tests. This will be turned off in system test. 
7863          turn_on_local_dir_test = False 
7864   
7865          if turn_on_local_dir_test: 
7866              ## Now check to local folder with None argument. 
7867              # Write input 
7868              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
7869   
7870              # Check the r2eff set files. 
7871              print("\nChecking the R2eff input set files.") 
7872              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
7873   
7874              # First check file exists 
7875              for dir, file in files: 
7876                  print(dir+sep+file) 
7877                  self.assert_(access(dir+sep+file, F_OK)) 
7878   
7879              ## Now check to local folder with dir argument. 
7880              # Write input 
7881              set_dir = "Test_ShereKhan" 
7882              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
7883   
7884              # Check the r2eff set files. 
7885              print("\nChecking the R2eff input set files.") 
7886              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
7887   
7888              # First check file exists 
7889              for dir, file in files: 
7890                  print(dir+sep+file) 
7891                  self.assert_(access(dir+sep+file, F_OK)) 
7892   
7893   
7894 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
7895          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
7896   
7897          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
7898          """ 
7899   
7900          # Reset. 
7901          self.interpreter.reset() 
7902   
7903          # Create the data pipe and load the base data. 
7904          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
7905          self.interpreter.state.load(data_path+sep+'r2eff_values') 
7906   
7907          # The model data pipe. 
7908          model = 'MMQ CR72' 
7909          pipe_name = "%s - relax_disp" % model 
7910          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
7911          self.interpreter.pipe.switch(pipe_name=pipe_name) 
7912   
7913          # Set the model. 
7914          self.interpreter.relax_disp.select_model(model=model) 
7915   
7916          # Cluster everything. 
7917          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
7918   
7919          # Copy the data. 
7920          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
7921   
7922          # Alias the spins. 
7923          spin135S = cdp.mol[0].res[0].spin[0] 
7924          spin135F = cdp.mol[0].res[0].spin[1] 
7925          spin137S = cdp.mol[0].res[1].spin[0] 
7926          spin137F = cdp.mol[0].res[1].spin[1] 
7927   
7928          # The R20 keys. 
7929          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
7930          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
7931   
7932          # Set the cluster specific parameters (only for the first spin). 
7933          spin135S.pA = 0.836591763632 
7934          spin135S.kex = 241.806525261 
7935   
7936          # Set the initial parameter values. 
7937          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
7938          spin135S.dw = 0.583003118785 
7939          spin135S.dwH = 0.0361441944301 
7940   
7941          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
7942          spin135F.dw = 0.805849745104 
7943          spin135F.dwH = 0.0215791945715 
7944   
7945          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
7946          spin137S.dw = 0.688107568372 
7947          spin137S.dwH = 0.0344463604043 
7948   
7949          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
7950          spin137F.dw = 0.94978299907 
7951          spin137F.dwH = 1.4818877939e-07 
7952   
7953          # Low precision optimisation. 
7954          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
7955   
7956          # Printout. 
7957          print("\n\nOptimised parameters:\n") 
7958          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
7959          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
7960          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
7961          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
7962          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
7963          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
7964          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
7965          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
7966          print("\n        # Set the cluster specific parameters (only for the first spin).") 
7967          print("        spin135S.pA = %s" % spin135S.pA) 
7968          print("        spin135S.kex = %s" % spin135S.kex) 
7969          print("\n        # Set the initial parameter values.") 
7970          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
7971          print("        spin135S.dw = %s" % spin135S.dw) 
7972          print("        spin135S.dwH = %s" % spin135S.dwH) 
7973          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
7974          print("        spin135F.dw = %s" % spin135F.dw) 
7975          print("        spin135F.dwH = %s" % spin135F.dwH) 
7976          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
7977          print("        spin137S.dw = %s" % spin137S.dw) 
7978          print("        spin137S.dwH = %s" % spin137S.dwH) 
7979          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
7980          print("        spin137F.dw = %s" % spin137F.dw) 
7981          print("        spin137F.dwH = %s" % spin137F.dwH) 
7982   
7983          # Checks for residue :135S. 
7984          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
7985          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
7986          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
7987          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
7988          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
7989          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
7990          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
7991   
7992          # Checks for residue :135F. 
7993          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
7994          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
7995          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
7996          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
7997          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
7998          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
7999          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8000   
8001          # Checks for residue :137S. 
8002          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8003          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8004          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8005          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8006          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8007          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8008          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8009   
8010          # Checks for residue :137F. 
8011          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8012          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8013          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8014          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8015          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8016          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8017          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8018   
8019   
8020 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8021          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8022   
8023          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8024          """ 
8025   
8026          # Reset. 
8027          self.interpreter.reset() 
8028   
8029          # Create the data pipe and load the base data. 
8030          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8031          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8032   
8033          # The model data pipe. 
8034          model = 'NS MMQ 2-site' 
8035          pipe_name = "%s - relax_disp" % model 
8036          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8037          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8038   
8039          # Set the model. 
8040          self.interpreter.relax_disp.select_model(model=model) 
8041   
8042          # Cluster everything. 
8043          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8044   
8045          # Copy the data. 
8046          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8047   
8048          # Alias the spins. 
8049          spin135S = cdp.mol[0].res[0].spin[0] 
8050          spin135F = cdp.mol[0].res[0].spin[1] 
8051          spin137S = cdp.mol[0].res[1].spin[0] 
8052          spin137F = cdp.mol[0].res[1].spin[1] 
8053   
8054          # The R20 keys. 
8055          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8056          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8057   
8058          # Set the cluster specific parameters (only for the first spin). 
8059          spin135S.pA = 0.847378444499757 
8060          spin135S.kex = 264.055604934724329 
8061   
8062          # Set the initial parameter values. 
8063          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8064          spin135S.dw = 0.585574008745351 
8065          spin135S.dwH = 0.000000000000002 
8066   
8067          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8068          spin135F.dw = 0.856699277665748 
8069          spin135F.dwH = 0.000000000582587 
8070   
8071          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8072          spin137S.dw = 0.772904450844973 
8073          spin137S.dwH = 0.183351478512970 
8074   
8075          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8076          spin137F.dw = 0.984568590342831 
8077          spin137F.dwH = 0.000000001993458 
8078   
8079          # Low precision optimisation. 
8080          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8081   
8082          # Printout. 
8083          print("\n\nOptimised parameters:\n") 
8084          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8085          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8086          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8087          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8088          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8089          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8090          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8091          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8092   
8093          # FIXME: Remove this temporary return and properly check the results. 
8094          return 
8095   
8096          # Checks for residue :135S. 
8097          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8098          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8099          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8100          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8101          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8102          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8103          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8104   
8105          # Checks for residue :135F. 
8106          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8107          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8108          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8109          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8110          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8111          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8112          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8113   
8114          # Checks for residue :137S. 
8115          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8116          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8117          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8118          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8119          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8120          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8121          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8122   
8123          # Checks for residue :137F. 
8124          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8125          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8126          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8127          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8128          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8129          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8130          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8131   
8132   
8133 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8134          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8135   
8136          # Setup the data. 
8137          self.setup_tp02_data_to_ns_r1rho_2site() 
8138   
8139          # Alias the spins. 
8140          spin1 = cdp.mol[0].res[0].spin[0] 
8141          spin2 = cdp.mol[0].res[1].spin[0] 
8142   
8143          # The R20 keys. 
8144          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8145          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8146   
8147          # Checks for residue :1. 
8148          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8149          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8150          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8151          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8152          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8153          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8154   
8155          # Checks for residue :2. 
8156          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8157          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8158          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8159          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8160          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8161          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8162   
8163   
8164 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8165          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8166   
8167          # Setup the data. 
8168          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8169   
8170          # Alias the spins. 
8171          spin1 = cdp.mol[0].res[0].spin[0] 
8172          spin2 = cdp.mol[0].res[1].spin[0] 
8173   
8174          # The R20 keys. 
8175          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8176          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8177   
8178          # Checks for residue :1. 
8179          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8180          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8181          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8182          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8183          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8184          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8185   
8186          # Checks for residue :2. 
8187          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8188          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8189          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8190          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8191          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8192          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8193   
8194   
8195 -    def test_tp02_data_to_mp05(self): 
8196          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8197   
8198          # Fixed time variable and the models. 
8199          ds.fixed = True 
8200          ds.models = ['R2eff', 'MP05'] 
8201   
8202          # Execute the script. 
8203          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8204   
8205          # Switch back to the data pipe for the optimisation. 
8206          self.interpreter.pipe.switch('MP05 - relax_disp') 
8207   
8208          # The equivalent MP05 parameters. 
8209          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8210          pA = [0.775055484521586, 0.500000000036595] 
8211          kex = [1235.20361276079, 2378.31403454691] 
8212          delta_omega = [7.08194146569694, 5.4083562844306] 
8213          chi2 = [0.0370400968727768, 0.182141732163934] 
8214   
8215          # Alias the spins. 
8216          spin1 = cdp.mol[0].res[0].spin[0] 
8217          spin2 = cdp.mol[0].res[1].spin[0] 
8218   
8219          # The R20 keys. 
8220          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8221          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8222   
8223          # Printout. 
8224          print("\n\nOptimised parameters:\n") 
8225          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8226          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8227          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8228          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8229          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8230          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8231          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8232   
8233          # Check each spin. 
8234          spin_index = 0 
8235          for spin, spin_id in spin_loop(return_id=True): 
8236              # Printout. 
8237              print("\nSpin %s." % spin_id) 
8238   
8239              # Check the fitted parameters. 
8240              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8241              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8242              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8243              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8244              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8245              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8246   
8247              # Increment the spin index. 
8248              spin_index += 1 
8249   
8250   
8251 -    def test_tp02_data_to_tap03(self): 
8252          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8253   
8254          # Fixed time variable and the models. 
8255          ds.fixed = True 
8256          ds.models = ['R2eff', 'TAP03'] 
8257   
8258          # Execute the script. 
8259          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8260   
8261          # Switch back to the data pipe for the optimisation. 
8262          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8263   
8264          # The equivalent TAP03 parameters. 
8265          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8266          pA = [0.775042569092891, 0.500000000229685] 
8267          kex = [1235.20852748765, 2379.47085580169] 
8268          delta_omega = [7.08176806468445, 5.40708372863538] 
8269          chi2 = [0.0371366837083293, 0.182212857256044] 
8270   
8271          # Alias the spins. 
8272          spin1 = cdp.mol[0].res[0].spin[0] 
8273          spin2 = cdp.mol[0].res[1].spin[0] 
8274   
8275          # The R20 keys. 
8276          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8277          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8278   
8279          # Printout. 
8280          print("\n\nOptimised parameters:\n") 
8281          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8282          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8283          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8284          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8285          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8286          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8287          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8288   
8289          # Switch to the 'MP05' model data pipe, then check for each spin. 
8290          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8291          spin_index = 0 
8292          for spin, spin_id in spin_loop(return_id=True): 
8293              # Printout. 
8294              print("\nSpin %s." % spin_id) 
8295   
8296              # Check the fitted parameters. 
8297              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8298              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8299              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8300              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8301              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8302              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8303   
8304              # Increment the spin index. 
8305              spin_index += 1 
8306   
8307   
8308 -    def test_tp02_data_to_tp02(self): 
8309          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8310   
8311          # Fixed time variable. 
8312          ds.fixed = True 
8313   
8314          # Execute the script. 
8315          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8316   
8317          # The original parameters. 
8318          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8319          pA = 0.7654321 
8320          kex = 1234.56789 
8321          delta_omega = [7.0, 9.0] 
8322   
8323          # The R20 keys. 
8324          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8325          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8326   
8327          # Switch to the 'TP02' model data pipe, then check for each spin. 
8328          self.interpreter.pipe.switch('TP02 - relax_disp') 
8329          spin_index = 0 
8330          for spin, spin_id in spin_loop(return_id=True): 
8331              # Printout. 
8332              print("\nSpin %s." % spin_id) 
8333   
8334              # Check the fitted parameters. 
8335              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8336              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8337              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8338              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8339   
8340              # Increment the spin index. 
8341              spin_index += 1 
8342   
8343   
8344 -    def test_value_write_calc_rotating_frame_params_int(self): 
8345          """System test of the value.write function to write intensities for an R1rho setup. 
8346          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8347   
8348          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8349          """ 
8350   
8351          # Load the state. 
8352          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8353          self.interpreter.state.load(statefile, force=True) 
8354   
8355          # Set filepaths. 
8356          int_filepath = ds.tmpdir+sep+'int.out' 
8357   
8358          # Write out the intensity parameter file. 
8359          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8360          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8361   
8362          # Test the file exists. 
8363          self.assert_(access(int_filepath, F_OK)) 
8364   
8365          # Open the files for testing. 
8366          int_file = open(int_filepath, 'r') 
8367   
8368          # Loop over the intensity file to test values. 
8369          for line in int_file: 
8370              # Skip lines starting with #. 
8371              if line[0] == "#": 
8372                  continue 
8373   
8374              # Split the line 
8375              linesplit = line.split() 
8376   
8377              # Assume values 
8378              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8379                  self.assertEqual(linesplit[5], "115571.4") 
8380              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8381                  self.assertEqual(linesplit[5], "68377.52") 
8382              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8383                  self.assertEqual(linesplit[5], "9141.689") 
8384              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8385                  self.assertEqual(linesplit[5], "29123.77") 
8386              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8387                  self.assertEqual(linesplit[5], "58914.94") 
8388   
8389          # Close files 
8390          int_file.close() 
8391   
8392   
8393 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8394          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8395   
8396          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8397          """ 
8398   
8399          # Load the state. 
8400          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8401          self.interpreter.state.load(statefile, force=True) 
8402   
8403          # Set filepaths. 
8404          theta_filepath = ds.tmpdir+sep+'theta.out' 
8405   
8406          # Write out the theta parameter file. 
8407          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8408   
8409          # Test the file exists. 
8410          self.assert_(access(theta_filepath, F_OK)) 
8411   
8412          # Open the files for testing. 
8413          theta_file = open(theta_filepath, 'r') 
8414   
8415          # Loop over the theta file to test values. 
8416          for line in theta_file: 
8417              # Skip lines starting with #. 
8418              if line[0] == "#": 
8419                  continue 
8420              # Print lines, not including newline character. 
8421              print(line[:-1]) 
8422   
8423              # Split the line 
8424              linesplit = line.split() 
8425   
8426              # Assume values 
8427              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8428                  self.assertNotEqual(linesplit[5], "None") 
8429              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8430                  self.assertNotEqual(linesplit[5], "None") 
8431              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8432                  self.assertNotEqual(linesplit[5], "None") 
8433              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8434                  self.assertNotEqual(linesplit[5], "None") 
8435              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8436                  self.assertNotEqual(linesplit[5], "None") 
8437   
8438          # Close files 
8439          theta_file.close() 
8440   
8441   
8442 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
8443          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
8444   
8445          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8446          """ 
8447   
8448          # Load the state. 
8449          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8450          self.interpreter.state.load(statefile, force=True) 
8451   
8452          # Set filepaths. 
8453          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
8454   
8455          # Write out the w_eff parameter file. 
8456          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8457   
8458          # Test the file exists. 
8459          self.assert_(access(w_eff_filepath, F_OK)) 
8460   
8461          # Open the files for testing. 
8462          w_eff_file = open(w_eff_filepath, 'r') 
8463   
8464          # Loop over the w_eff file to test values. 
8465          for line in w_eff_file: 
8466              # Skip lines starting with #. 
8467              if line[0] == "#": 
8468                  continue 
8469              # Print lines, not including newline character. 
8470              print(line[:-1]) 
8471   
8472              # Split the line 
8473              linesplit = line.split() 
8474   
8475              # Assume values 
8476              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8477                  self.assertNotEqual(linesplit[5], "None") 
8478              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8479                  self.assertNotEqual(linesplit[5], "None") 
8480              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8481                  self.assertNotEqual(linesplit[5], "None") 
8482              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8483                  self.assertNotEqual(linesplit[5], "None") 
8484              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8485                  self.assertNotEqual(linesplit[5], "None") 
8486   
8487          # Close files 
8488          w_eff_file.close() 
8489   
8490   
8491 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
8492          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
8493   
8494          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8495          """ 
8496   
8497          # Load the state. 
8498          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
8499          self.interpreter.state.load(statefile, force=True) 
8500   
8501          # Set pipe name, bundle and type. 
8502          pipe_name = 'base pipe' 
8503          pipe_bundle = 'relax_disp' 
8504          pipe_type = 'relax_disp' 
8505   
8506          # The path to the data files. 
8507          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
8508   
8509          # Deselect all spins 
8510          self.interpreter.deselect.all() 
8511   
8512          # Specify spins to be selected. 
8513          select_spin_ids = [ 
8514          ":13@N", 
8515          ":15@N", 
8516          ":16@N", 
8517          ":25@N", 
8518          ":26@N", 
8519          ":28@N", 
8520          ":39@N", 
8521          ":40@N", 
8522          ":41@N", 
8523          ":43@N", 
8524          ":44@N", 
8525          ":45@N", 
8526          ":49@N", 
8527          ":52@N", 
8528          ":53@N"] 
8529   
8530          # Reverse the selection for the spins. 
8531          for curspin in select_spin_ids: 
8532              print("Selecting spin %s"%curspin) 
8533              self.interpreter.deselect.reverse(spin_id=curspin) 
8534   
8535          # Read the R1 data 
8536          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
8537   
8538          # The dispersion models. 
8539          MODELS = ['R2eff'] 
8540   
8541          # The grid search size (the number of increments per dimension). 
8542          GRID_INC = 4 
8543   
8544          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
8545          MC_NUM = 3 
8546   
8547          # Model selection technique. 
8548          MODSEL = 'AIC' 
8549   
8550          # Execute the auto-analysis (fast). 
8551          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8552          OPT_FUNC_TOL = 1e-1 
8553          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
8554          OPT_MAX_ITERATIONS = 1000 
8555          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
8556   
8557          # Run the analysis. 
8558          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
8559   
8560          ## Check for file creation 
8561          # Set filepaths. 
8562          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
8563          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
8564   
8565          # Test the files exists. 
8566          self.assert_(access(theta_filepath, F_OK)) 
8567          self.assert_(access(w_eff_filepath, F_OK)) 
8568   
8569          # Open the files for testing. 
8570          theta_file = open(theta_filepath, 'r') 
8571          theta_result = [ 
8572              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
8573              "#\n", 
8574              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8575              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8576              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8577              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8578              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8579              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8580              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8581              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8582              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
8583              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8584              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
8585              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
8586              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8587              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8588              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8589              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8590              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8591              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
8592              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
8593              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8594              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
8595              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8596              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8597              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8598              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8599              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8600              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8601              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8602              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8603              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8604              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
8605              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
8606              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
8607              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8608              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
8609              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
8610              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
8611              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8612              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8613              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
8614              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8615              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8616              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
8617              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
8618              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8619              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8620              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8621              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8622              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8623          ] 
8624          # Check the created theta file. 
8625          lines = theta_file.readlines() 
8626          for i in range(len(lines)): 
8627              # Test lines starting with # 
8628              if theta_result[i][0] == "#": 
8629                  self.assertEqual(theta_result[i], lines[i]) 
8630              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8631              if theta_result[i] == lines[i]: 
8632                  self.assertEqual(theta_result[i], lines[i]) 
8633              # If the line is not equal each other, make a slower comparison of values. 
8634              else: 
8635                  # Print lines if they don't match. To help find differences. 
8636                  print(theta_result[i]) 
8637                  print(lines[i]) 
8638   
8639                  # First test first 62 characters containing spin information 
8640                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
8641   
8642                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8643                  theta_result_s = theta_result[i][62:].split()[::2] 
8644                  print(theta_result_s ) 
8645                  lines_s = lines[i][62:].split()[::2] 
8646                  print(lines_s) 
8647                  # Loop over the value elements 
8648                  for j in range(len(lines_s)): 
8649                      print(theta_result_s[j], lines_s[j]) 
8650                      # Assume a precision to digits. 
8651                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
8652   
8653          # Close file 
8654          theta_file.close() 
8655   
8656          w_eff_file = open(w_eff_filepath, 'r') 
8657          w_eff_result = [ 
8658              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
8659              "#\n", 
8660              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8661              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8662              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8663              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8664              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8665              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8666              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8667              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8668              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
8669              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8670              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
8671              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
8672              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8673              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8674              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8675              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8676              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8677              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
8678              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
8679              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8680              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
8681              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8682              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8683              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8684              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8685              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8686              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8687              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8688              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8689              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8690              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
8691              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
8692              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
8693              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8694              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
8695              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
8696              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
8697              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8698              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8699              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
8700              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8701              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8702              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
8703              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
8704              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8705              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8706              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8707              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8708              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8709          ] 
8710          # Check the created w_eff file. 
8711          lines = w_eff_file.readlines() 
8712          for i in range(len(lines)): 
8713              # Test lines starting with # 
8714              if w_eff_result[i][0] == "#": 
8715                  self.assertEqual(w_eff_result[i], lines[i]) 
8716              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8717              if w_eff_result[i] == lines[i]: 
8718                  self.assertEqual(w_eff_result[i], lines[i]) 
8719              # If the line is not equal each other, make a slower comparison of values. 
8720              else: 
8721                  # Print lines if they don't match. To help find differences. 
8722                  print(w_eff_result[i]) 
8723                  print(lines[i]) 
8724   
8725                  # First test first 62 characters containing spin information 
8726                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
8727   
8728                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8729                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
8730                  print(w_eff_result_s ) 
8731                  lines_s = lines[i][62:].split()[::2] 
8732                  print(lines_s) 
8733                  # Loop over the value elements 
8734                  for j in range(len(lines_s)): 
8735                      print(w_eff_result_s[j], lines_s[j]) 
8736                      # Assume a precision to digits. 
8737                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
8738   
8739          # Close file 
8740          w_eff_file.close() 
8741   
8742   
8743 -    def verify_estimate_r2eff_err_compare_mc(self): 
8744          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
8745   
8746          This follows Task 7822. 
8747          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
8748   
8749          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
8750          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
8751          """ 
8752   
8753          # Load the data. 
8754          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
8755   
8756          # Set pipe name, bundle and type. 
8757          pipe_name = 'base pipe' 
8758          pipe_bundle = 'relax_disp' 
8759          pipe_type = 'relax_disp' 
8760   
8761          # Create the data pipe. 
8762          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
8763   
8764          file = data_path + '1_setup_r1rho_GUI.py' 
8765          self.interpreter.script(file=file, dir=None) 
8766   
8767          # Deselect all spins. 
8768          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
8769   
8770          # Select one spin. 
8771          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
8772   
8773          # Set the model. 
8774          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8775   
8776          # Check if intensity errors have already been calculated. 
8777          check_intensity_errors() 
8778   
8779          # Do a grid search. 
8780          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
8781   
8782          # Set algorithm. 
8783          min_algor = 'Newton' 
8784          constraints = True 
8785          if constraints: 
8786              min_options = ('%s'%(min_algor),) 
8787              #min_algor = 'Log barrier' 
8788              min_algor = 'Method of Multipliers' 
8789              scaling_matrix = assemble_scaling_matrix(scaling=True) 
8790   
8791              # Collect spins 
8792              all_spin_ids = [] 
8793              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8794                  all_spin_ids.append(spin_id) 
8795   
8796              spins = spin_ids_to_containers(all_spin_ids[:1]) 
8797   
8798              # Get constraints 
8799              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
8800          else: 
8801              min_options = () 
8802              A, b = None, None 
8803          min_options = () 
8804          sim_boot = 200 
8805          scaling_list = [1.0, 1.0] 
8806   
8807          # Minimise. 
8808          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
8809   
8810          # Loop over old err attributes. 
8811          err_attr_list = ['r2eff_err', 'i0_err'] 
8812   
8813          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8814              # Loop over old err attributes. 
8815              for err_attr in err_attr_list: 
8816                  if hasattr(cur_spin, err_attr): 
8817                      delattr(cur_spin, err_attr) 
8818   
8819          # Collect the estimation data from boot. 
8820          my_dic = {} 
8821          param_key_list = [] 
8822          est_keys = [] 
8823          est_key = '-2' 
8824          est_keys.append(est_key) 
8825          spin_id_list = [] 
8826   
8827          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8828              # Add key to dic. 
8829              my_dic[spin_id] = {} 
8830   
8831              # Add key for estimate. 
8832              my_dic[spin_id][est_key] = {} 
8833   
8834              # Add spin key to list. 
8835              spin_id_list.append(spin_id) 
8836   
8837              # Generate spin string. 
8838              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
8839   
8840              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
8841                  # Generate the param_key. 
8842                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
8843   
8844                  # Append key. 
8845                  param_key_list.append(param_key) 
8846   
8847                  # Add key to dic. 
8848                  my_dic[spin_id][est_key][param_key] = {} 
8849   
8850                  values = [] 
8851                  errors = [] 
8852                  times = [] 
8853                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
8854                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
8855                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
8856                      times.append(time) 
8857   
8858                  # Convert to numpy array. 
8859                  values = asarray(values) 
8860                  errors = asarray(errors) 
8861                  times = asarray(times) 
8862   
8863                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
8864                  i0 = getattr(cur_spin, 'i0')[param_key] 
8865   
8866                  R_m_sim_l = [] 
8867                  I0_m_sim_l = [] 
8868                  for j in range(sim_boot): 
8869                      if j in range(0, 100000, 100): 
8870                          print("Simulation %i"%j) 
8871                      # Start minimisation. 
8872   
8873                      # Produce errors 
8874                      I_err = [] 
8875                      for j, error in enumerate(errors): 
8876                          I_error = gauss(values[j], error) 
8877                          I_err.append(I_error) 
8878                      # Convert to numpy array. 
8879                      I_err = asarray(I_err) 
8880   
8881                      x0 = [r2eff, i0] 
8882                      setup(num_params=len(x0), num_times=len(times), values=I_err, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
8883   
8884                      # Ref input. 
8885                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
8886                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
8887                      # l: Lower bound constraint vector (l <= x <= u). 
8888                      # u: Upper bound constraint vector (l <= x <= u). 
8889                      # c: User supplied constraint function. 
8890                      # dc: User supplied constraint gradient function. 
8891                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=func, dfunc=dfunc, d2func=d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
8892   
8893                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
8894                      R_m_sim_l.append(R_m_sim_j) 
8895                      I0_m_sim_l.append(I0_m_sim_j) 
8896   
8897                  # Get stats on distribution. 
8898                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
8899                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
8900                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
8901                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
8902   
8903          # Estimate R2eff errors. 
8904          self.interpreter.relax_disp.r2eff_err_estimate() 
8905   
8906          est_key = '-1' 
8907          est_keys.append(est_key) 
8908   
8909          # Collect data. 
8910          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8911              # Add key for estimate. 
8912              my_dic[spin_id][est_key] = {} 
8913   
8914              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
8915                  # Generate the param_key. 
8916                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
8917   
8918                  # Add key to dic. 
8919                  my_dic[spin_id][est_key][param_key] = {} 
8920   
8921                  # Get the value. 
8922                  # Loop over err attributes. 
8923                  for err_attr in err_attr_list: 
8924                      if hasattr(cur_spin, err_attr): 
8925                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
8926                      else: 
8927                          get_err_attr = 0.0 
8928   
8929                      # Save to dic. 
8930                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
8931   
8932   
8933          # Make Carlo Simulations number 
8934          mc_number_list = list(range(0, 1000, 250)) 
8935   
8936          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
8937   
8938          # Loop over the Monte Carlo simulations: 
8939          for number in mc_number_list: 
8940              # First delete old simulations. 
8941              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8942                  # Loop over old err attributes. 
8943                  for err_attr in err_attr_list: 
8944                      if hasattr(cur_spin, err_attr): 
8945                          delattr(cur_spin, err_attr) 
8946   
8947                  # Loop over the simulated attributes. 
8948                  for sim_attr in sim_attr_list: 
8949                      if hasattr(cur_spin, sim_attr): 
8950                          delattr(cur_spin, sim_attr) 
8951   
8952              self.interpreter.monte_carlo.setup(number=number) 
8953              self.interpreter.monte_carlo.create_data() 
8954              self.interpreter.monte_carlo.initial_values() 
8955              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
8956              self.interpreter.eliminate() 
8957              self.interpreter.monte_carlo.error_analysis() 
8958   
8959              est_key = '%i'%number 
8960              est_keys.append(est_key) 
8961   
8962              # Collect data. 
8963              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8964                  # Add key for estimate. 
8965                  my_dic[spin_id][est_key] = {} 
8966   
8967                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
8968                      # Generate the param_key. 
8969                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
8970   
8971                      # Add key to dic. 
8972                      my_dic[spin_id][est_key][param_key] = {} 
8973   
8974                      # Get the value. 
8975                      # Loop over err attributes. 
8976                      for err_attr in err_attr_list: 
8977                          if hasattr(cur_spin, err_attr): 
8978                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
8979                          else: 
8980                              get_err_attr = 0.0 
8981   
8982                          # Save to dic. 
8983                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
8984   
8985          # Set what to extract. 
8986          err_attr = err_attr_list[0] 
8987   
8988          # Define list with text. 
8989          text_list = [] 
8990   
8991          # Now loop through the data. 
8992          for spin_id in spin_id_list: 
8993              for est_key in est_keys: 
8994                  # Define list to pickup data. 
8995                  r2eff_err_list = [] 
8996   
8997                  for param_key in param_key_list: 
8998                      # Get the value. 
8999                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9000   
9001                      # Add to list. 
9002                      r2eff_err_list.append(r2eff_err) 
9003   
9004                  # Sum the list 
9005                  sum_array = sum(array(r2eff_err_list)) 
9006   
9007                  # Join floats to string. 
9008                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9009   
9010                  # Define print string. 
9011                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9012                  text_list.append(text) 
9013   
9014   
9015          # Now print. 
9016          filepath = NamedTemporaryFile(delete=False).name 
9017          # Open the files for testing. 
9018          w_file = open(filepath, 'w') 
9019   
9020          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9021   
9022          for text in text_list: 
9023              # Print. 
9024              print(text) 
9025   
9026              # Write to file. 
9027              w_file.write(text+"\n") 
9028   
9029          # Close files 
9030          w_file.close() 
9031   
9032          print("Filepath is: %s"%filepath) 
9033          print("Start 'gnuplot' and write:") 
9034          print("set term dumb") 
9035          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9036   
9037   
9038 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9039          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9040   
9041          # Check the kex value of residue 52 
9042          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9043   
9044          # Print results for each model. 
9045          print("\n\n################") 
9046          print("Printing results") 
9047          print("################\n") 
9048          for model in models: 
9049              # Skip R2eff model. 
9050              if model == MODEL_R2EFF: 
9051                  continue 
9052   
9053              # Switch to pipe. 
9054              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9055              print("\nModel: %s" % (model)) 
9056   
9057              # Loop over the spins. 
9058              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9059                  # Generate spin string. 
9060                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9061   
9062                  # Loop over the parameters. 
9063                  print("Optimised parameters for spin: %s" % (spin_string)) 
9064                  for param in cur_spin.params + ['chi2']: 
9065                      # Get the value. 
9066                      if param in ['r1', 'r2']: 
9067                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9068                              # Generate the R20 key. 
9069                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9070   
9071                              # Get the value. 
9072                              value = getattr(cur_spin, param)[r20_key] 
9073   
9074                              # Print value. 
9075                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9076   
9077                              # Compare values. 
9078                              if spin_id == ':52@N': 
9079                                  if param == 'r1': 
9080                                      if model == MODEL_NOREX: 
9081                                          if r2eff_estimate == 'direct': 
9082                                              self.assertAlmostEqual(value, 1.46138805) 
9083                                          elif r2eff_estimate == 'MC2000': 
9084                                              self.assertAlmostEqual(value, 1.46328102) 
9085                                          elif r2eff_estimate == 'chi2_pyt': 
9086                                              self.assertAlmostEqual(value, 1.43820629) 
9087                                      elif model == MODEL_DPL94: 
9088                                          if r2eff_estimate == 'direct': 
9089                                              self.assertAlmostEqual(value, 1.44845742) 
9090                                          elif r2eff_estimate == 'MC2000': 
9091                                              self.assertAlmostEqual(value, 1.45019848) 
9092                                          elif r2eff_estimate == 'chi2_pyt': 
9093                                              self.assertAlmostEqual(value, 1.44666512) 
9094                                      elif model == MODEL_TP02: 
9095                                          if r2eff_estimate == 'direct': 
9096                                              self.assertAlmostEqual(value, 1.54354392) 
9097                                          elif r2eff_estimate == 'MC2000': 
9098                                              self.assertAlmostEqual(value, 1.54352369) 
9099                                          elif r2eff_estimate == 'chi2_pyt': 
9100                                              self.assertAlmostEqual(value, 1.55964020) 
9101                                      elif model == MODEL_TAP03: 
9102                                          if r2eff_estimate == 'direct': 
9103                                              self.assertAlmostEqual(value, 1.54356410) 
9104                                          elif r2eff_estimate == 'MC2000': 
9105                                              self.assertAlmostEqual(value, 1.54354367) 
9106                                          elif r2eff_estimate == 'chi2_pyt': 
9107                                              self.assertAlmostEqual(value, 1.55967157) 
9108                                      elif model == MODEL_MP05: 
9109                                          if r2eff_estimate == 'direct': 
9110                                              self.assertAlmostEqual(value, 1.54356416) 
9111                                          elif r2eff_estimate == 'MC2000': 
9112                                              self.assertAlmostEqual(value, 1.54354372) 
9113                                          elif r2eff_estimate == 'chi2_pyt': 
9114                                              self.assertAlmostEqual(value, 1.55967163) 
9115                                      elif model == MODEL_NS_R1RHO_2SITE: 
9116                                          if r2eff_estimate == 'direct': 
9117                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9118                                          elif r2eff_estimate == 'MC2000': 
9119                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9120                                          elif r2eff_estimate == 'chi2_pyt': 
9121                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9122   
9123                                  elif param == 'r2': 
9124                                      if model == MODEL_NOREX: 
9125                                          if r2eff_estimate == 'direct': 
9126                                              self.assertAlmostEqual(value, 11.48392439) 
9127                                          elif r2eff_estimate == 'MC2000': 
9128                                              self.assertAlmostEqual(value, 11.48040934) 
9129                                          elif r2eff_estimate == 'chi2_pyt': 
9130                                              self.assertAlmostEqual(value, 11.47224488) 
9131                                      elif model == MODEL_DPL94: 
9132                                          if r2eff_estimate == 'direct': 
9133                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9134                                          elif r2eff_estimate == 'MC2000': 
9135                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9136                                          elif r2eff_estimate == 'chi2_pyt': 
9137                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9138                                      elif model == MODEL_TP02: 
9139                                          if r2eff_estimate == 'direct': 
9140                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9141                                          elif r2eff_estimate == 'MC2000': 
9142                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9143                                          elif r2eff_estimate == 'chi2_pyt': 
9144                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9145                                      elif model == MODEL_TAP03: 
9146                                          if r2eff_estimate == 'direct': 
9147                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9148                                          elif r2eff_estimate == 'MC2000': 
9149                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9150                                          elif r2eff_estimate == 'chi2_pyt': 
9151                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9152                                      elif model == MODEL_MP05: 
9153                                          if r2eff_estimate == 'direct': 
9154                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9155                                          elif r2eff_estimate == 'MC2000': 
9156                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9157                                          elif r2eff_estimate == 'chi2_pyt': 
9158                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9159                                      elif model == MODEL_NS_R1RHO_2SITE: 
9160                                          if r2eff_estimate == 'direct': 
9161                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9162                                          elif r2eff_estimate == 'MC2000': 
9163                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9164                                          elif r2eff_estimate == 'chi2_pyt': 
9165                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9166   
9167                      # For all other parameters. 
9168                      else: 
9169                          # Get the value. 
9170                          value = getattr(cur_spin, param) 
9171   
9172                          # Print value. 
9173                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9174   
9175                          # Compare values. 
9176                          if spin_id == ':52@N': 
9177                              if param == 'phi_ex': 
9178                                  if model == MODEL_DPL94: 
9179                                      if r2eff_estimate == 'direct': 
9180                                          self.assertAlmostEqual(value, 0.07599563) 
9181                                      elif r2eff_estimate == 'MC2000': 
9182                                          self.assertAlmostEqual(value, 0.07561937) 
9183                                      elif r2eff_estimate == 'chi2_pyt': 
9184                                          self.assertAlmostEqual(value, 0.12946061) 
9185   
9186                              elif param == 'pA': 
9187                                  if model == MODEL_TP02: 
9188                                      if r2eff_estimate == 'direct': 
9189                                          self.assertAlmostEqual(value, 0.88827040) 
9190                                      elif r2eff_estimate == 'MC2000': 
9191                                          self.assertAlmostEqual(value, 0.88807487) 
9192                                      elif r2eff_estimate == 'chi2_pyt': 
9193                                          self.assertAlmostEqual(value, 0.87746233) 
9194                                  elif model == MODEL_TAP03: 
9195                                      if r2eff_estimate == 'direct': 
9196                                          self.assertAlmostEqual(value, 0.88828922) 
9197                                      elif r2eff_estimate == 'MC2000': 
9198                                          self.assertAlmostEqual(value, 0.88809318) 
9199                                      elif r2eff_estimate == 'chi2_pyt': 
9200                                          self.assertAlmostEqual(value, 0.87747558) 
9201                                  elif model == MODEL_MP05: 
9202                                      if r2eff_estimate == 'direct': 
9203                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9204                                      elif r2eff_estimate == 'MC2000': 
9205                                          self.assertAlmostEqual(value, 0.88809321) 
9206                                      elif r2eff_estimate == 'chi2_pyt': 
9207                                          self.assertAlmostEqual(value, 0.87747562) 
9208                                  elif model == MODEL_NS_R1RHO_2SITE: 
9209                                      if r2eff_estimate == 'direct': 
9210                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9211                                      elif r2eff_estimate == 'MC2000': 
9212                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9213                                      elif r2eff_estimate == 'chi2_pyt': 
9214                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9215   
9216                              elif param == 'dw': 
9217                                  if model == MODEL_TP02: 
9218                                      if r2eff_estimate == 'direct': 
9219                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9220                                      elif r2eff_estimate == 'MC2000': 
9221                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9222                                      elif r2eff_estimate == 'chi2_pyt': 
9223                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9224                                  elif model == MODEL_TAP03: 
9225                                      if r2eff_estimate == 'direct': 
9226                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9227                                      elif r2eff_estimate == 'MC2000': 
9228                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9229                                      elif r2eff_estimate == 'chi2_pyt': 
9230                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9231                                  elif model == MODEL_MP05: 
9232                                      if r2eff_estimate == 'direct': 
9233                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9234                                      elif r2eff_estimate == 'MC2000': 
9235                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9236                                      elif r2eff_estimate == 'chi2_pyt': 
9237                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9238                                  elif model == MODEL_NS_R1RHO_2SITE: 
9239                                      if r2eff_estimate == 'direct': 
9240                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9241                                      elif r2eff_estimate == 'MC2000': 
9242                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9243                                      elif r2eff_estimate == 'chi2_pyt': 
9244                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9245   
9246                              elif param == 'kex': 
9247                                  if model == MODEL_DPL94: 
9248                                      if r2eff_estimate == 'direct': 
9249                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9250                                      elif r2eff_estimate == 'MC2000': 
9251                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9252                                      elif r2eff_estimate == 'chi2_pyt': 
9253                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9254                                  elif model == MODEL_TP02: 
9255                                      if r2eff_estimate == 'direct': 
9256                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9257                                      elif r2eff_estimate == 'MC2000': 
9258                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9259                                      elif r2eff_estimate == 'chi2_pyt': 
9260                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9261                                  elif model == MODEL_TAP03: 
9262                                      if r2eff_estimate == 'direct': 
9263                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9264                                      elif r2eff_estimate == 'MC2000': 
9265                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9266                                      elif r2eff_estimate == 'chi2_pyt': 
9267                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9268                                  elif model == MODEL_MP05: 
9269                                      if r2eff_estimate == 'direct': 
9270                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9271                                      elif r2eff_estimate == 'MC2000': 
9272                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9273                                      elif r2eff_estimate == 'chi2_pyt': 
9274                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9275                                  elif model == MODEL_NS_R1RHO_2SITE: 
9276                                      if r2eff_estimate == 'direct': 
9277                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9278                                      elif r2eff_estimate == 'MC2000': 
9279                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9280                                      elif r2eff_estimate == 'chi2_pyt': 
9281                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9282   
9283                              elif param == 'chi2': 
9284                                  if model == MODEL_NOREX: 
9285                                      if r2eff_estimate == 'direct': 
9286                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9287                                      elif r2eff_estimate == 'MC2000': 
9288                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9289                                      elif r2eff_estimate == 'chi2_pyt': 
9290                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9291                                  elif model == MODEL_DPL94: 
9292                                      if r2eff_estimate == 'direct': 
9293                                          self.assertAlmostEqual(value, 179.47041241) 
9294                                      elif r2eff_estimate == 'MC2000': 
9295                                          self.assertAlmostEqual(value, 710.24767560) 
9296                                      elif r2eff_estimate == 'chi2_pyt': 
9297                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9298                                  elif model == MODEL_TP02: 
9299                                      if r2eff_estimate == 'direct': 
9300                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9301                                      elif r2eff_estimate == 'MC2000': 
9302                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9303                                      elif r2eff_estimate == 'chi2_pyt': 
9304                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9305                                  elif model == MODEL_TAP03: 
9306                                      if r2eff_estimate == 'direct': 
9307                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9308                                      elif r2eff_estimate == 'MC2000': 
9309                                          self.assertAlmostEqual(value, 114.27987534) 
9310                                      elif r2eff_estimate == 'chi2_pyt': 
9311                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9312                                  elif model == MODEL_MP05: 
9313                                      if r2eff_estimate == 'direct': 
9314                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9315                                      elif r2eff_estimate == 'MC2000': 
9316                                          self.assertAlmostEqual(value, 114.28002272) 
9317                                      elif r2eff_estimate == 'chi2_pyt': 
9318                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9319                                  elif model == MODEL_NS_R1RHO_2SITE: 
9320                                      if r2eff_estimate == 'direct': 
9321                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9322                                      elif r2eff_estimate == 'MC2000': 
9323                                          self.assertAlmostEqual(value, 134.14368365) 
9324                                      elif r2eff_estimate == 'chi2_pyt': 
9325                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9326   
9327   
9328          # Print the final pipe. 
9329          model = 'final' 
9330          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9331          print("\nFinal pipe") 
9332   
9333          # Loop over the spins. 
9334          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9335              # Generate spin string. 
9336              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9337   
9338              # Loop over the parameters. 
9339              print("Optimised model for spin: %s" % (spin_string)) 
9340              param = 'model' 
9341   
9342              # Get the value. 
9343              value = getattr(cur_spin, param) 
9344              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9345   
9346   
9347          ### Now check some of the written out files. 
9348          file_names = ['r1rho_prime', 'r1'] 
9349   
9350          for file_name_i in file_names: 
9351   
9352              # Make the file name. 
9353              file_name = "%s.out" % file_name_i 
9354   
9355              # Get the file path. 
9356              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9357   
9358              # Test the file exists. 
9359              print("Testing file access to: %s"%file_path) 
9360              self.assert_(access(file_path, F_OK)) 
9361   
9362              # Now open, and compare content, line by line. 
9363              file_prod = open(file_path) 
9364              lines_prod = file_prod.readlines() 
9365              file_prod.close() 
9366   
9367              # Loop over the lines. 
9368              for i, line in enumerate(lines_prod): 
9369                  # Make the string test 
9370                  line_split = line.split() 
9371   
9372                  # Continue for comment lines. 
9373                  if line_split[0] == "#": 
9374                      print(line), 
9375                      continue 
9376   
9377                  # Assign the split of the line. 
9378                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9379                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9380   
9381                  if res_num == '52': 
9382                      # Assert that the value is not None. 
9383                      self.assertNotEqual(val, 'None') 
9384